Electronic device, method, and storage medium for providing information about medication taken

Abstract

Provided are an electronic device, a method, and a storage medium for providing information about medication taken. The electronic device comprises a display and a memory for storing instructions. The instructions, when executed individually or collectively by at least one processor, are configured to cause the electronic device to receive information about a medication on the basis of a first input. The instructions are configured to cause the electronic device to acquire a medication category related to the medication on the basis of the information about the medication. The instructions are configured to cause the electronic device to receive a second input indicating information about medication taking time. The instructions are configured to cause the electronic device to acquire biometric information about a user. The instructions are configured to cause the electronic device to acquire, on the basis of the biometric information and the information about medication taking time, a first score according to a first factor applied to a plurality of medication categories and a second score according to a second factor applied to the medication category related to the medication. The instructions are configured to cause the electronic device to provide, via the display, a first visual object indicating the first score according to the first factor and the second score according to the second factor.

Description

Electronic device, method and storage medium for providing information on medication

[0001] The present disclosure relates to electronic devices, methods and storage media, and for example, to electronic devices, methods and storage media for providing information on medication.

[0002] In addition to handheld electronic devices, wearable electronic devices worn on the user's body are becoming increasingly popular. Various types of electronic devices can include functions that measure the user's biosignals. With growing interest in health management, electronic devices can provide analysis of measured biosignals, information on ingested substances (e.g., food, medication, etc.), and / or health status.

[0003] The above information may be provided merely as background information to aid in understanding the present disclosure. None of the above is claimed as prior art related to the present disclosure or can be used in determining prior art.

[0004] An electronic device according to various embodiments of the present document may include a display, at least one processor including a processing circuit, and a memory storing instructions. The instructions may be configured to cause the electronic device to receive information about a drug based on a first input. The instructions may be configured to cause the electronic device to obtain a drug category related to the drug based on the information about the drug. The instructions may be configured to cause the electronic device to receive a second input indicating information about the time at which the drug was taken. The instructions may be configured to cause the electronic device to obtain biometric information of a user. The instructions may be configured to cause the electronic device to obtain a first score according to a first factor applied to a plurality of drug categories and a second score according to a second factor applied to the drug category related to the drug based on the biometric information and the information about the time at which the drug was taken. The above instructions may be configured to cause the electronic device to provide, through the display, a first visual object representing the first score according to the first argument and the second score according to the second argument.

[0005] A method for providing information on a medication according to various embodiments of the present document may include receiving information on the medication based on a first input. The method may include obtaining a medication category related to the medication based on the information on the medication. The method may include receiving a second input indicating information on a time at which the medication was taken. The method may include obtaining biometric information of a user. The method may include obtaining a first score according to a first factor applied to a plurality of medication categories and a second score according to a second factor applied to the medication category related to the medication based on the biometric information and the information on the time at which the medication was taken. The method may include providing a first visual object representing the first score according to the first factor and the second score according to the second factor.

[0006] A non-transitory computer-readable storage medium having recorded thereon a program for performing a method for providing information on a medication according to various embodiments of the present document may include an operation for receiving information on a medication based on a first input. The storage medium may include an operation for obtaining a drug category related to the medication based on the information on the medication. The storage medium may include an operation for receiving a second input indicating information on a time at which the medication was taken. The storage medium may include an operation for obtaining biometric information of a user. The storage medium may include an operation for obtaining a first score according to a first factor applied to a plurality of medication categories and a second score according to a second factor applied to the medication category related to the medication based on the biometric information and the information on the time at which the medication was taken. The storage medium may include an operation for providing a first visual object representing the first score according to the first factor and the second score according to the second factor.

[0007] The above and other aspects, features, and advantages of specific embodiments of the present disclosure will become more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which:

[0008] FIG. 1 is a block diagram of an electronic device within a network environment according to various embodiments.

[0009] FIG. 2 is a block diagram illustrating the configuration of an electronic device according to various embodiments.

[0010] FIGS. 3a, 3b, 3c, 3d, 3e, and 3f are drawings illustrating an operation of adding information on a medication according to various embodiments.

[0011] FIG. 4A and FIG. 4B are diagrams illustrating operations for managing a medication schedule according to various embodiments.

[0012] FIG. 5 is a diagram illustrating a system for receiving biometric information from a wearable device according to various embodiments.

[0013] FIGS. 6A, 6B, 6C, 6D, and 6E are diagrams illustrating UIs of analysis data according to various embodiments.

[0014] Figure 7 is a drawing explaining the UI before and after the time of onset of effect of the taken medicine according to various embodiments.

[0015] FIG. 8a and FIG. 8b are drawings explaining an operation of receiving information from a user according to various embodiments.

[0016] FIG. 9 is a diagram illustrating a UI of analysis data including side effect information according to various embodiments.

[0017] FIG. 10A and FIG. 10B are diagrams illustrating an operation of providing information on related drugs according to various embodiments.

[0018] FIG. 11 is a diagram illustrating a UI for notifying a time of taking medication after receiving side effect information according to various embodiments.

[0019] FIG. 12 is a diagram illustrating an operation of providing comparative data before and after taking a drug according to various embodiments.

[0020] Figure 13 is a flowchart illustrating a method for providing information on medication according to various embodiments.

[0021] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings so that those skilled in the art can easily implement the present disclosure. However, the present disclosure may be implemented in various different forms and is not limited to the embodiments described herein. In connection with the description of the drawings, the same or similar reference numerals may be used for identical or similar components. Furthermore, in the drawings and related descriptions, descriptions of well-known functions and configurations may be omitted for clarity and conciseness.

[0022] FIG. 1 is a block diagram of an electronic device (101) within a network environment (100) according to various embodiments. Referring to FIG. 1, in the network environment (100), the electronic device (101) may communicate with the electronic device (102) via a first network (198) (e.g., a short-range wireless communication network), or may communicate with at least one of the electronic device (104) or the server (108) via a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) via the server (108). According to one embodiment, the electronic device (101) may include a processor (120), a memory (130), an input module (150), an audio output module (155), a display module (160), an audio module (170), a sensor module (176), an interface (177), a connection terminal (178), a haptic module (179), a camera module (180), a power management module (188), a battery (189), a communication module (190), a subscriber identification module (196), or an antenna module (197). In some embodiments, the electronic device (101) may omit at least one of these components (e.g., the connection terminal (178)), or may have one or more other components added. In some embodiments, some of these components (e.g., the sensor module (176), the camera module (180), or the antenna module (197)) may be integrated into one component (e.g., the display module (160)).

[0023] The processor (120) may include various processing circuits and / or multiple processors. For example, the term "processor" as used herein, including in the claims, may include various processing circuits including at least one processor. Here, one or more of the at least one processor may, individually and / or collectively, perform various functions described herein in a distributed manner. When the terms "processor," "at least one processor," and "one or more processors" as used herein are described as performing a number of functions, these terms may encompass, by way of example and without limitation, situations where one processor performs some of the recited functions and other processor(s) perform other of the recited functions, as well as situations where a single processor may perform all of the recited functions. Furthermore, the at least one processor may include a combination of processors that perform various recited / disclosed functions, for example, in a distributed manner. The at least one processor may execute program instructions to achieve or perform various functions.

[0024] The processor (120) may, for example, execute software (e.g., a program (140)) to control at least one other component (e.g., a hardware or software component) of the electronic device (101) connected to the processor (120) and perform various data processing or calculations. According to one embodiment, as at least a part of the data processing or calculations, the processor (120) may store commands or data received from other components (e.g., a sensor module (176) or a communication module (190)) in a volatile memory (132), process the commands or data stored in the volatile memory (132), and store result data in a non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., a central processing unit or an application processor) or a secondary processor (123) (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor)) that can operate independently or together therewith. For example, if the electronic device (101) includes a main processor (121) and a secondary processor (123), the secondary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a specified function. The secondary processor (123) may be implemented separately from the main processor (121) or as a part thereof.

[0025] The auxiliary processor (123) may control at least a portion of functions or states associated with at least one component (e.g., a display module (160), a sensor module (176), or a communication module (190)) of the electronic device (101), for example, on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. In one embodiment, the auxiliary processor (123) (e.g., an image signal processor or a communication processor) may be implemented as a part of another functionally related component (e.g., a camera module (180) or a communication module (190)). In one embodiment, the auxiliary processor (123) (e.g., a neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. The artificial intelligence models may be generated through machine learning. This learning can be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or can be performed through a separate server (e.g., server (108)). The learning algorithm can include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model can include multiple artificial neural network layers.The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to, or alternatively to, a hardware structure, an artificial intelligence model may include a software structure.

[0026] The memory (130) can store various data used by at least one component (e.g., the processor (120) or the sensor module (176)) of the electronic device (101). The data can include, for example, software (e.g., the program (140)) and input data or output data for commands related thereto. The memory (130) can include a volatile memory (132) or a nonvolatile memory (134). The nonvolatile memory (134) can include at least one internal memory (136) and an external memory (138).

[0027] The program (140) may be stored as software in the memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0028] The input module (150) can receive commands or data to be used in a component of the electronic device (101) (e.g., a processor (120)) from an external source (e.g., a user) of the electronic device (101). The input module (150) can include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0029] The audio output module (155) can output audio signals to the outside of the electronic device (101). The audio output module (155) can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. In one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0030] The display module (160) can visually provide information to an external party (e.g., a user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling the device. In one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of a force generated by the touch.

[0031] The audio module (170) can convert sound into an electrical signal, or vice versa, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150), output sound through the sound output module (155), or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphone) directly or wirelessly connected to the electronic device (101).

[0032] The sensor module (176) can detect the operating status (e.g., power or temperature) of the electronic device (101) or the external environmental status (e.g., user status) and generate an electrical signal or data value corresponding to the detected status. According to one embodiment, the sensor module (176) can include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0033] The interface (177) may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device (101) with an external electronic device (e.g., the electronic device (102)). In one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0034] The connection terminal (178) may include a connector through which the electronic device (101) may be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0035] A haptic module (179) can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that a user can perceive through tactile or kinesthetic sensations. In one embodiment, the haptic module (179) can include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

[0036] The camera module (180) can capture still images and videos. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0037] The power management module (188) can manage power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least a part of a power management integrated circuit (PMIC).

[0038] A battery (189) may power at least one component of the electronic device (101). In one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0039] The communication module (190) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may operate independently from the processor (120) (e.g., application processor) and may include one or more communication processors that support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (194) (e.g., a local area network (LAN) communication module, or a power line communication module). Among these communication modules, the corresponding communication module can communicate with an external electronic device (104) via a first network (198) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (199) (e.g., a long-range communication network such as a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules can be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can verify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) by using subscriber information (e.g., an international mobile subscriber identity (IMSI)) stored in the subscriber identification module (196).

[0040] The wireless communication module (192) can support 5G networks and next-generation communication technologies following the 4G network, such as NR access technology (new radio access technology). The NR access technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module (192) can support, for example, a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate. The wireless communication module (192) can support various technologies for securing performance in a high-frequency band, such as beamforming, massive multiple-input and multiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), an external electronic device (e.g., the electronic device (104)), or a network system (e.g., the second network (199)). According to one embodiment, the wireless communication module (192) can support a peak data rate (e.g., 20 Gbps or more) for eMBB realization, a loss coverage (e.g., 164 dB or less) for mMTC realization, or a U-plane latency (e.g., 0.5 ms or less for downlink (DL) and uplink (UL), or 1 ms or less for round trip) for URLLC realization.

[0041] The antenna module (197) can transmit or receive signals or power to or from an external device (e.g., an external electronic device). In one embodiment, the antenna module (197) may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). In one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as the first network (198) or the second network (199), may be selected from the plurality of antennas by, for example, the communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. In some embodiments, in addition to the radiator, another component (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module (197).

[0042] According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent a first side (e.g., a bottom side) of the printed circuit board and capable of supporting a designated high frequency band (e.g., a mmWave band), and a plurality of antennas (e.g., an array antenna) disposed on or adjacent a second side (e.g., a top side or a side side) of the printed circuit board and capable of transmitting or receiving signals in the designated high frequency band.

[0043] At least some of the above components can be interconnected and exchange signals (e.g., commands or data) with each other via a communication method between peripheral devices (e.g., a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0044] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) via a server (108) connected to a second network (199). Each of the external electronic devices (102 or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations executed in the electronic device (101) may be executed in one or more of the external electronic devices (102, 104, or 108). For example, when the electronic device (101) is to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device (101) may, instead of or in addition to executing the function or service itself, request one or more external electronic devices to perform the function or at least a part of the service. One or more external electronic devices that receive the request may execute at least a portion of the requested function or service, or an additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may process the result as is or additionally and provide it as at least a portion of a response to the request. For this purpose, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used, for example. The electronic device (101) may provide an ultra-low latency service by using distributed computing or mobile edge computing, for example. In one embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or a neural network. According to one embodiment, the external electronic device (104) or the server (108) may be included in the second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0045] Electronic devices according to the various embodiments disclosed in this document may take various forms. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. Electronic devices according to the embodiments of this document are not limited to the aforementioned devices.

[0046] FIG. 2 is a block diagram illustrating the configuration of an electronic device according to various embodiments.

[0047] Referring to FIG. 2, the electronic device (200) may include a display (210), a memory (220), and a processor (230) (e.g., including a processing circuit).

[0048] The display (210) (e.g., the display module (160) of FIG. 1) can output data processed by the processor (230) (e.g., the processor (120) of FIG. 1) as an image. For example, the display (210) can display a UI (user interface) for entering (or registering) a medication, a visual object including information about the entered medication and / or analysis data analyzed based on the user's biometric information, etc.

[0049] For example, the analysis data may include a first factor, a first score according to the first factor, a second factor, and / or a second score according to the second factor. For example, the first factor may include a factor that is commonly applied to multiple drug categories. For example, the first factor may include activity information, sleep information, condition information, and / or calorie information. The first score according to the first factor may include a score that quantifies the first factor. For example, the second factor may include a factor that is applicable to a drug category related to the drug. For example, the second factor may include weight information, blood sugar information, blood pressure information, heart rate information, sleep information, and / or self-diagnosis information. The second score according to the second factor may include a score that quantifies the second factor. For example, the visual object may be an object that visualizes and displays the analysis data for the convenience of the user. The visual object may include the first factor, the first score according to the first factor, the second factor, and / or the second score according to the second factor. Visual objects may include charts, treemaps, heatmaps, analysis tables, datasheets, graphs, and / or histograms.

[0050] The memory (220) (e.g., the memory (130) of FIG. 1) can store data, algorithms, programs, commands (instructions), etc. that perform functions of the electronic device (200) (e.g., the electronic device (101) of FIG. 1). The commands, etc. stored in the memory (220) can be loaded into the processor (230) and executed by the processor (230). As an example, the memory (220) can store information on medication, a dosing schedule, a history of taking one or more medications, biometric information, self-diagnosis information input by the user, analysis data, and / or visual objects.

[0051] The processor (230) can control each component of the electronic device (200). The electronic device (101) can include one or more processors (230). One or more processors (230) can individually or collectively execute instructions. For example, the processor (230) can correspond to multiple processors that collectively perform multiple functions by dividing them among the processors.

[0052] The processor (1230) may include various processing circuits and / or multiple processors. For example, the term "processor" as used herein, including in the claims, may include various processing circuits including at least one processor. Here, one or more of the at least one processor may, individually and / or collectively, perform various functions described herein in a distributed manner. When the terms "processor," "at least one processor," and "one or more processors" as used herein are described as performing a number of functions, these terms may encompass, by way of example and without limitation, situations where one processor performs some of the recited functions and other processor(s) perform other of the recited functions, as well as situations where a single processor may perform all of the recited functions. Furthermore, the at least one processor may include a combination of processors that perform various recited / disclosed functions, for example, in a distributed manner. The at least one processor may execute program instructions to achieve or perform various functions.

[0053] For example, the processor (230) may receive information about a drug based on an input (e.g., a first user input). As an example, the processor (230) may receive information about a drug through input of a drug name by a user, photographing (or scanning) a drug name using a camera, and / or linking with a prescription. The processor (230) may obtain a drug category related to the drug based on the received drug information. As an example, the processor (230) may classify the drug into a preset (or specified) drug category based on the received drug information. As an example, an external device (e.g., a server or a database) may classify the drug category based on the drug information. The processor (230) may receive information about the drug category from the external device. The processor (230) may obtain classification information about the drug from a database connected through the external device (e.g., a server), or may obtain the drug category based on the drug information.

[0054] For example, a drug category may include a first drug category and a second drug category. The first drug category may be a drug category that includes qualitative information (e.g., self-diagnosis information) in the analysis data obtained after taking the drug, and the second drug category may be a drug category that includes quantitative information in the analysis data. For example, if the category of the drug being taken is related to pain relief, the analysis data may include qualitative information including the degree of pain symptom relief, and thus the category related to pain relief may be classified into the first drug category. If the category of the drug being taken is related to weight loss, the analysis data may include weight loss information, and thus the drug category related to weight loss may be classified into the second drug category. Drugs classified into the first and second drug categories may be further classified into subcategories based on the type of drug and / or the corresponding symptom. For example, drugs related to pain relief may be classified into the first drug category and the analgesic category. Drugs related to weight loss may be classified into the second drug category and the diet drug category.

[0055] For example, information about a medication may include a dosing schedule. The processor (230) may provide a medication reminder to the user based on the dosing schedule. As an example, the dosing reminder UI may include an entry for inputting whether or not to take the medication. The processor (230) may receive a dosing completion input (e.g., a second user input) from the user. For example, the processor (230) may receive a dosing completion input including the time the medication was taken directly from the user. For example, when the processor (230) receives a dosing completion input from the user, the processor (230) may determine the time information of the electronic device (200) as the time information for taking the medication. The dosing completion input received from the user may indicate the time information for taking the medication.

[0056] The processor (230) can acquire the user's biometric information. For example, the processor (230) can continuously and / or continuously acquire the user's biometric information at regular intervals or at preset time points. The processor (230) can determine whether the acquired biometric information is biometric information before or after taking the medication based on the medication schedule.

[0057] The processor (230) may obtain a first score according to a first factor commonly applied to multiple drug categories based on the acquired biometric information and information on the time at which the drug was taken, and a second score according to a second factor applied to a drug category related to the drug taken. For example, the first factor may include activity information, sleep information, condition information, and / or calorie information. The score according to the first factor may include a score calculated based on the first factor. For example, the second factor may include weight information, blood sugar information, blood pressure information, heart rate information, sleep information, and / or self-diagnosis information. The score according to the second factor may include a score calculated based on the second factor. The processor (230) may provide a visual object representing the first score according to the first factor and the second score according to the second factor through the display (210). For example, the visual object may include a chart, a treemap, a heatmap, an analysis table, a data sheet, a graph, and / or a histogram.

[0058] The effects of a medication may occur a certain amount of time after the time of administration. The processor (230) may determine the time of onset of effect based on the medication and / or the dosing schedule. For example, if the medication is classified as a first medication category, the processor (230) may receive self-diagnosis information from the user. As an example, if the medication is classified as a first medication category, the processor (230) may determine the time of onset of effect from the time of administration of the medication. If the time of onset of effect is satisfied, the processor (230) may receive self-diagnosis information from the user. The processor (230) may provide a visual object including the self-diagnosis information as a second factor.

[0059] For example, in relation to a short-term medication (e.g., a painkiller), the electronic device (200) may calculate a first score according to a first factor and a second score according to a second factor based on biometric information acquired after the time of onset of effect (e.g., 2 hours after the time of administration). The electronic device (200) may generate a visual object based on the calculated first score and second score. For example, the score at the time of onset of effect (or the score after the onset of effect) included in the visual object may be the user's most recent update score confirmed at the time of onset of effect (or after the time of onset of effect).

[0060] For example, in relation to a medication that is taken continuously (e.g., a sleeping pill), the electronic device (200) can calculate a first score according to a first factor and a second score according to a second factor from biometric information periodically acquired from the time of starting the medication (e.g., the day of starting the medication). The electronic device (200) can average each of the calculated first and second scores according to a regular cycle (e.g., daily) and generate a visual object based on the calculated average value. For example, the first score according to the first factor and the second score according to the second factor can be updated at a regular cycle (e.g., daily). In other words, the electronic device (200) can obtain the most recently updated first score and second score based on the user's biometric information acquired at the time of onset of the effect of the medication or after the time of taking the medication.

[0061] The second factor may include different information depending on the drug category associated with the medication. For example, if the drug category of the medication is related to pain relief, the processor (230) may receive self-diagnosis information from the user, including the degree of pain relief. The processor (230) may provide the received self-diagnosis information as a second score based on the second factor. For example, if the drug category of the medication is related to weight loss, the processor (230) may determine the weight loss based on the user's biometric information. The processor (230) may provide weight information including the weight loss as a second score based on the second factor. For example, if the drug category of the medication is related to insomnia, the processor (230) may determine the deep sleep time based on the user's biometric information. The processor (230) may provide sleep information including the deep sleep time as the second factor. For example, if the drug category of the medication is related to blood pressure, the processor (230) may determine blood pressure information based on the user's biometric information. The processor (230) may provide blood pressure information as a second score based on a second factor. For example, if the medication category of the medication is related to diabetes, the processor (230) may determine blood sugar information based on the user's biometric information. The processor (230) may provide blood sugar information as a second score based on a second factor. For example, if the medication category of the medication is related to arrhythmia, the processor (230) may determine pulse regularity based on the user's biometric information. The processor (230) may provide heart rate information including pulse regularity as a second score based on the second factor.

[0062] For example, the processor (230) may store the user's previously taken medication history and analysis data of the taken medication in the memory (220). Upon the user's request, the processor (230) may determine related medications included in the same medication category (or, same type, corresponding to the same symptom) as the currently taken medication, and identify analysis data of the related medications. The processor (230) may provide the user with analysis data of one or more related medications. For example, the processor (230) may determine the effect of the medication based on a first score according to a first factor included in the analysis data and / or a second score according to a second factor. The processor (230) may receive information on side effects from the user. The processor (230) may determine the side effects of the medication based on the received information on side effects. The processor (230) may generate a visual object representing the analysis data based on the effect and / or side effects of the medication, and provide the generated visual object to the user through the display (210).

[0063] For example, the processor (230) may receive analysis data of related medication taken by another person through a communication interface (e.g., the communication module (190) of FIG. 1). The other person may include a family member or another person with a predetermined correlation or higher. As an example, the predetermined correlation may include a correlation of overall biometric information of the user and the other person, a correlation of biometric information related to symptoms of the user and the other person, a correlation of a first score according to a first factor of the user and the other person and a second score according to a second factor, and / or a correlation of a side effect of the user and the other person that is greater than a predetermined value. The received analysis data may include information on the effects and / or side effects of the medication. The processor (230) may generate a visual object representing analysis data of related medication taken by the other person based on the effects and / or side effects of the medication, and provide the generated visual object to the user through the display (210).

[0064] For example, the processor (230) may provide information on a drug included in a drug category according to a symptom input by a user based on the effectiveness and / or side effects by using analysis data of the drug learned by the artificial intelligence model. The processor (230) may provide information on a single drug, or may provide information on a combination of multiple drugs. For example, if the combination of multiple drugs includes a main drug and a sub-drug, the processor (230) may provide information on the combination of multiple drugs by displaying the main drug and the sub-drug so as to be distinguished from each other. For example, the processor (230) may distinguish the main drug and the sub-drug by using different colors, line thicknesses, and / or sizes.

[0065] For example, the processor (230) may receive information about side effects from the user and store biometric information related to the side effects in the memory (220). As an example, the processor (230) may periodically obtain biometric information including heart rate information. If the obtained biometric information of the user is within a preset range with respect to the biometric information related to the side effects, the processor (230) may provide a notification to the user. As an example, if the heart rate of the user increases from about 80 to about 100 after taking medication, the processor (230) may store biometric information including the heart rate information that has increased to about 100. If the preset range is 5%, the processor (230) may provide a notification to the user when the heart rate becomes 95 or higher.

[0066] The electronic device, method, and storage medium of this document can be used to determine the effects, efficacy, and health indices of medications by linking them with biometric information. The electronic device, method, and storage medium of this document can also provide information about other medications based on their efficacy and / or side effects.

[0067] The effects of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0068] FIGS. 3a, 3b, 3c, 3d, 3e, and 3f are drawings illustrating an operation of adding information on a medication according to various embodiments.

[0069] Referring to FIG. 3A, a UI for adding medication information is illustrated. The electronic device (200) may display a UI for adding medication information based on input (e.g., user input). The UI for adding medication information may include a medication name input item (1), a medication name scan item (3) using a camera, and an input item (5) linked to a prescription.

[0070] Referring to FIG. 3B, a UI for entering a drug name is illustrated. When the drug name input item (1) in FIG. 3A is selected, the electronic device (200) may display a UI for entering a drug name. For example, a first area (3010) of the UI may display a list of drug names related to input characters (or numbers), and a second area (3020) may display a character input area. As an example, the input area may be implemented as a keyboard, a keypad, or a writing area. The electronic device (200) may display a list of drug names including characters entered in the input area in the first area (3010). For example, the list of drug names may be stored in a memory (220) or an external device (e.g., the electronic device (102) of FIG. 1, the server (108)). The electronic device (200) can load (or receive) a drug name from the memory (220) or an external device based on the input characters and display it in the first area (3010). When one drug name from the list of drug names is selected, the electronic device (200) can receive information about the drug corresponding to the selected drug name from the external device.

[0071] Referring to FIG. 3C, a camera that photographs a medicine bottle (91) is illustrated. When the medicine name scan item (3) using the camera in FIG. 3A is selected, the electronic device (200) can drive the camera (e.g., the camera module (180) of FIG. 1). The medicine name can be displayed on the medicine bottle (91). The electronic device (200) can recognize the medicine name displayed on the medicine bottle (91). For example, the electronic device (200) can recognize the medicine name from an image that photographs the medicine name displayed on the medicine bottle (91) or recognize the medicine name from a preview image that includes the medicine name. When the electronic device (200) recognizes the medicine name, it can receive information about the medicine corresponding to the recognized medicine name from an external device.

[0072] Referring to FIG. 3D, a UI (3050) for entering detailed medication information is illustrated. Medication information received from an external device may only include general information. Even for the same medication, the method of taking the medication may vary depending on the patient's condition and / or the severity of symptoms. When medication information is received by entering the medication name or scanning the medication name using a camera, the electronic device (200) may display a UI (3050) for entering detailed medication information. For example, the UI (3050) for entering detailed medication information may include items for determining medication dosage / type, setting medication shape, and setting medication schedule. The electronic device (200) may receive detailed medication information, including the medication schedule, from the user on the UI (3050) for entering detailed medication information.

[0073] Referring to FIG. 3E, an electronic device (200) that receives information about a drug in connection with a prescription is illustrated. When an input item (5) associated with a prescription is selected in FIG. 3A, the electronic device (200) can communicate with an external device (300) containing information about the prescription. The electronic device (200) can receive information about the drug from the information about the prescription contained in the external device (300). The information about the prescription can include information about the drug dosage and / or the dosing schedule. The electronic device (200) can receive not only general information about the drug but also detailed information about the drug, including the dosing schedule, from the information about the prescription.

[0074] Referring to FIG. 3F, a UI (3070) displaying a list of input medications is illustrated. For example, the list of input medications may include information on the name of the medication, type of medication, shape of the medication, dosage, and / or schedule of the medication. The electronic device (200) may classify the input medications into a plurality of groups according to preset criteria, and display each group of medications separately on the UI (3070) displaying the list of medications. For example, the electronic device (200) may classify the input medications into a group of medications taken at regular intervals and a group of medications taken regularly when necessary. The electronic device (200) may display the group of medications taken periodically and the group of medications taken regularly separately on the UI (3070) displaying the list of medications.

[0075] FIG. 4A and FIG. 4B are diagrams illustrating operations for managing a medication schedule according to various embodiments.

[0076] Referring to FIG. 4A, a medication reminder UI (3090) and a medication completion UI (3100) are illustrated. The electronic device (200) may provide a medication reminder to the user based on the entered medication schedule. For example, if the medication schedule for AAA medication is 1:30 PM, the electronic device (200) may provide a medication reminder for AAA medication at 1:30 PM. The electronic device (200) may display the medication reminder UI (3090) and output a notification sound and / or vibration. For example, the medication reminder UI (3090) may include information on the medication time and / or medication. In addition, the medication reminder UI (3090) may include a not-taken input item (11) and a completed medication input item (13). For example, if the not-taken input item (11) is selected, the electronic device (200) may determine that the user has not taken the medication. When the medication completion input item (13) is selected, the electronic device (200) may determine that the user has taken the medication and display the medication history UI (3100). For example, the electronic device (200) may receive information on the time at which the medication was taken directly from the user along with the selection of the medication completion input item (13). For example, when the medication completion input item (13) is selected by the user, the electronic device (200) may determine the time information of the electronic device (200) as information on the time at which the medication was taken. The medication history UI (3100) may include a history of medications that have been taken. For example, the medication history UI (3100) may include an area (3101) including medication completion information for the current medication and / or an area (3103) including medication completion information for the previous medication. As an example, the areas (3101, 3103) including medication completion information may include information on the medication and / or the time of taking.

[0077] Referring to FIG. 4B, a dosage notification UI (3120) and a dosage completion UI (3130) displayed on a wearable device are illustrated. For example, the electronic device (200) may be a wearable device. The wearable device may include, for example and without limitation, a smartwatch and / or a smart ring.

[0078] Even if the electronic device (200) is a wearable device, the electronic device (200) can perform operations similar to those described in FIG. 4A. For example, the electronic device (200) can provide a medication reminder to the user based on the entered medication schedule and display a medication reminder UI (3120). The medication reminder UI (3120) can include a not-taken input item (15) and a completed medication input item (17). For example, if the not-taken input item (15) is selected, the electronic device (200) can determine that the user has not taken the medication. If the completed medication input item (17) is selected, the electronic device (200) can determine that the user has taken the medication and display a medication history UI (3130). For example, the medication history UI (3130) may include an area (3131) including information on completion of taking the current medication and / or an area (3133) including information on completion of taking the previous medication.

[0079] FIG. 5 is a diagram illustrating a system for receiving biometric information from a wearable device according to various embodiments.

[0080] Referring to FIG. 5, for example, the electronic device (200) may be implemented as a smartphone. When the electronic device (200) is implemented as a smartphone, the electronic device (200) includes a communication interface (e.g., the communication module (190) of FIG. 1) and may receive biometric information (or health data) from the wearable device (400). For example, the wearable device (400) may be worn on the user's body. The wearable device (400) includes a sensor (e.g., the sensor module (176) of FIG. 1) and may acquire biometric information of the user. For example, the biometric information may include weight information, blood sugar information, blood pressure information, heart rate information, and / or sleep information. The wearable device (400) may transmit the acquired biometric information to the electronic device (200) through a communication interface (e.g., the communication module (190) of FIG. 1). The electronic device (200) may generate analysis data including a first score according to a first factor and a second score according to a second factor based on the received biometric information, and may generate a visual object representing the generated analysis data. The electronic device (200) may provide the generated visual object to the user. For example, the visual object may include a chart, a treemap, a heatmap, an analysis table, a data sheet, a graph, and / or a histogram. As an example, the wearable device (400) may generate analysis data based on the acquired biometric information. The wearable device (400) may transmit the generated analysis data to the electronic device (200) via a communication interface (e.g., the communication module (190) of FIG. 1). The electronic device (200) may generate a visual object representing the received analysis data. The electronic device (200) may provide the generated visual object to the user. As an example, the wearable device (400) may generate analysis data based on the acquired biometric information, and may generate a visual object representing the analysis data.The wearable device (400) can transmit the generated visual object to the electronic device (200) via a communication interface (e.g., the communication module (190) of FIG. 1). The electronic device (200) can provide the received visual object to the user.

[0081] For example, the electronic device may be implemented as a wearable device (400). When the electronic device is implemented as a wearable device (400), the electronic device may obtain the user's biometric information. As an example, the wearable device (400) may transmit the obtained user's biometric information to an external device (e.g., the electronic device (200) of FIG. 5) through a communication interface (e.g., the communication module (190) of FIG. 1). The external device that receives the user's biometric information may generate analysis data and / or a visual object representing the analysis data and provide the generated visual object to the user. As an example, the wearable device (400) may generate analysis data based on the obtained user's biometric information. The wearable device (400) may transmit the generated analysis data to the external device through a communication interface (e.g., the communication module (190) of FIG. 1). The external device that receives the analysis data may generate a visual object representing the analysis data and provide the generated visual object to the user. As an example, the wearable device (400) may generate analysis data and / or visual objects representing the analysis data based on the acquired user's biometric information. The wearable device (400) may transmit the generated visual objects to an external device via a communication interface (e.g., the communication module (190) of FIG. 1). The external device that receives the visual objects may provide the received visual objects to the user. For example, if the number of analysis data and / or visual objects is greater than or equal to a preset number, the wearable device (400) may transmit the analysis data and / or visual objects to the external device. If there is a lot of information related to the analysis data and / or visual objects, the wearable device (400) may transmit the analysis data and / or visual objects to the external device so that the external device may display them.As an example, the wearable device (400) may transmit analysis data and / or visual objects containing a plurality of pieces of information depending on the information and / or dosage of other medications to an external device.

[0082] For example, if the electronic device (200) is implemented as a smartphone, the electronic device (200) may include a sensor. If the electronic device (200) includes a sensor, the electronic device (200) may acquire biometric information of the user using the sensor. As an example, the electronic device (200) may provide the user with a notification for measuring biometric information at a preset time and / or at a regular interval. When the sensor comes into contact with the user's body, the electronic device (200) may acquire biometric information. The electronic device (200) may generate analysis data based on the acquired biometric information and generate a visual object based on the generated analysis data.

[0083] FIGS. 6A, 6B, 6C, 6D, and 6E are diagrams illustrating UIs of analysis data according to various embodiments.

[0084] For example, the analysis data may include a first factor commonly applied to multiple drug categories, a first score according to the first factor, a second factor applied to a drug category related to the drug, and a second score according to the second factor. As an example, the first factor may include activity information, sleep information, condition information, and / or calorie information, and the second factor may include weight information, blood sugar information, blood pressure information, heart rate information, sleep information, and / or self-diagnosis information. For example, the activity information may indicate the user's activity status. For example, the activity information may include the number of steps, the amount of exercise, and / or the type of exercise. The activity score may be an indicator that quantifies the user's activity status. The activity score may be calculated based on activity calories according to the number of steps and the amount of exercise, and a weighting according to the intensity of the exercise. The sleep information may indicate the user's sleep quality. For example, the sleep information may include total sleep time, sleep regularity, sleep onset time, deep sleep percentage, wake-up percentage during sleep, REM sleep percentage, number of sleep cycles, sleep heart rate, and / or sleep heart rate variability. A sleep score may be a quantitative indicator of a user's sleep quality. The sleep score may be calculated based on total sleep time, percentage of deep sleep, percentage of awakenings during sleep, percentage of REM sleep, and / or number of sleep cycles. Condition information may indicate a user's condition at the start of the day (e.g., energy or vitality), and the condition score may be referred to as an energy score or vitality score. The condition score may be an indicator that quantifies the user's condition at the start of the day. The condition score may be calculated based on the user's sleep and activity information from the previous day. Calorie information may indicate calorie intake and expenditure. For example, calorie information may include calorie intake relative to recommended calorie intake, basal metabolic rate, and / or calorie expenditure. The calorie score may be an indicator of calorie intake and expenditure.Calorie scores can be calculated based on calorie intake, basal metabolic rate, and / or calorie expenditure compared to recommended calorie intake. Calorie scores can be presented as points or as an indicator of calorie balance.

[0085] Referring to FIG. 6A, a UI (3150) of analysis data of a weight loss drug is illustrated. The UI (3150) of analysis data of a weight loss drug may include an information area (3151) of the taken weight loss drug, a visual object area (3152) representing analysis data related to taking the weight loss drug, and a dosage schedule area (3153). As an example, the information area (3151) of the weight loss drug may include an image (or icon) (3156) of the weight loss drug, a name (3157) of the weight loss drug, a dosage (3158), and a drug information edit item (3159). For example, the drug information edit item (3159) may modify the image (or icon) (3156) of the weight loss drug, the name (3157) of the weight loss drug, and / or the dosage (3158). As an example, the visual object area (3152) may include a base area (3161) of the visual object, a pre-dosing visual object (3162) indicating a first score and a second score before taking the drug, and a post-dosing visual object (3163) indicating a first score and a second score after taking the drug. For example, a first factor of analysis data of a weight loss drug may include activity information, sleep information, condition information, and / or calorie information. A second factor may include weight information including a reduced weight. As an example, the base area (3161) of the visual object may be displayed in the form of a figure connecting a maximum value of the first score according to the first factor and a maximum value of the second score according to the second factor. The pre-dosing visual object (3162) and the post-dosing visual object (3163) may be displayed in the form of a figure connecting the first score and the second score, respectively. The electronic device (200) can provide a pre-administration visual object (3162) including a first score and a second score and a post-administration visual object (3163) including a first score and a second score as health indicators related to taking a weight loss drug.As an example, the dosing schedule area (3153) may include a dosing schedule associated with the currently displayed medication and may include an edit dosing schedule item (3166) that allows editing the dosing schedule.

[0086] Referring to FIG. 6B, a UI (3170) of analysis data of an insomnia medication is illustrated. The UI (3170) of analysis data of an insomnia medication may include an information area of ​​the insomnia medication and a visual object area of ​​analysis data related to taking the insomnia medication. For example, the visual object area of ​​the insomnia medication may include a pre-medication visual object (3171) indicating a first score and a second score before taking the medication and a post-medication visual object (3172) indicating a first score and a second score after taking the medication. For example, a first factor of the analysis data of the insomnia medication may include activity information, sleep information, condition information, and / or calorie information. A second factor may include sleep information including deep sleep time. The electronic device (200) may provide a pre-medication visual object (3171) including the first score and the second score and a post-medication visual object (3172) including the first score and the second score as health indicators related to taking the insomnia medication.

[0087] Referring to FIG. 6C, a UI (3190) for analysis data of a drug related to pain relief, excluding a score according to a second factor, is illustrated. For example, the second factor of the analysis data of a drug related to pain relief may include self-diagnosis information including the degree of pain symptom relief. The first factor of the drug related to pain relief may include activity information, sleep information, condition information, and / or calorie information. The self-diagnosis information may be qualitative information received from the user. For example, if the electronic device (200) does not receive the self-diagnosis information, the second score according to the second factor and the visual object before taking the drug may be omitted, and a visual object after taking the drug (3191) including the first score according to the first factor may be provided as a health indicator related to taking the pain relief drug. For example, the UI (3190) for analysis data of a drug related to pain relief may include an area (3193) for entering self-diagnosis information. The electronic device (200) can receive self-diagnosis information through the area (3193) for entering self-diagnosis information after the time for the effect of the medication has passed.

[0088] Referring to FIG. 6D , a UI (3200) of analysis data of a drug related to pain relief, including a second score according to a second factor, is illustrated. The electronic device (200) can receive self-diagnosis information through an area (3203) for entering self-diagnosis information in the UI (3200) of analysis data of a drug related to pain relief. When the electronic device (200) receives the self-diagnosis information, it can provide a visual object (3201) before administration including the first score and the second score and a visual object (3202) after administration including the first score and the second score as health indicators related to administration of the drug related to pain relief.

[0089] For example, if the medication is related to blood pressure, the electronic device (200) may provide visual objects before and after administration of analysis data that include blood pressure information as a second factor. If the medication is related to diabetes, the electronic device (200) may provide visual objects before and after administration of analysis data that include blood sugar information as a second factor. If the medication is related to arrhythmia, the electronic device (200) may provide visual objects before and after administration of analysis data that include heart rate information including pulse regularity as a second factor.

[0090] Referring to FIG. 6E, a UI (3210) of analysis data according to dosage is illustrated. The electronic device (200) may provide a plurality of visual objects (3211, 3212) including a first score according to a first factor and a second score according to a second factor according to dosage. As an example, as illustrated in FIG. 6E, the electronic device (200) may provide a first visual object (3211) including a first score and a second score when a 60 mg weight loss drug is taken, and a first visual object (3212) including a first score and a second score when a 120 mg weight loss drug is taken.

[0091] Figure 7 is a drawing explaining the UI before and after the time of onset of effect of the taken medicine according to various embodiments.

[0092] For example, the second factor of a drug classified as a first drug category may be self-diagnosis information. The self-diagnosis information may be a qualitative indicator of the effect felt by the user after taking the drug. The electronic device (200) may display an area (3231) for entering self-diagnosis information in the UI (3230) of analysis data for a drug classified as a first drug category (e.g., a drug related to pain relief). Since drugs require time to take effect after taking the drug, the electronic device (200) may receive self-diagnosis information from the user after the time of onset of effect of the drug.

[0093] For example, if the medication is classified as a first medication category, the electronic device (200) can determine the time of onset of effect from the time of taking the medication. For example, if the time of onset of effect of the medication is 2 hours, the electronic device (200) can deactivate the area (3231) for entering self-diagnosis information from the time of taking the medication to 2 hours before. If the area (3231) for entering self-diagnosis information is in the deactivated state, the electronic device (200) cannot receive self-diagnosis information, and thus, as described in FIG. 6C, can display a visual object excluding the second score according to the self-diagnosis information. If 2 hours have passed since the time of taking the medication, the electronic device (200) can activate the area (3231) for entering self-diagnosis information. If the area (3231) for entering self-diagnosis information is in the activated state, the electronic device (200) can receive self-diagnosis information. When the electronic device (200) receives self-diagnosis information, it can display a visual object including a second score according to the self-diagnosis information, as described in FIG. 6d.

[0094] FIG. 8a and FIG. 8b are drawings illustrating an operation of receiving information from a user according to various embodiments.

[0095] Referring to FIG. 8A, a self-diagnosis input UI (3270) is illustrated. For example, the electronic device (200) may display an area for entering self-diagnosis information in the UI of analysis data of a drug classified into the first drug category (e.g., a drug related to pain relief), and may receive self-diagnosis information through the area for entering self-diagnosis information.

[0096] As an example, the electronic device (200) may display a separate self-diagnosis input UI (3270) to receive self-diagnosis information from the user. As described above, medication may require time to take effect after taking the medication. The electronic device (200) may determine the time for the medication to take effect. When the time for the medication to take effect has elapsed, the electronic device (200) may provide a notification to the user guiding the user to enter self-diagnosis information and display the self-diagnosis input UI (3270). For example, the electronic device (200) may display multiple levels of symptom improvement after taking the medication and receive an input for selecting one level. As an example, the degree of symptom improvement may be divided into five levels depending on the degree of effect, from level 1, which represents no effect, to level 5, which represents very good. When the electronic device (200) receives an input from the user to select and save a level, the electronic device (200) may include the self-diagnosis information of the medication as a second factor in the analysis data and display a visual object including a second score according to the second factor.

[0097] Referring to FIG. 8B, a side effect input UI (3310) is illustrated. The electronic device (200) can receive side effect information when receiving self-diagnosis information. As an example, the electronic device (200) can receive side effect information separately from receiving self-diagnosis information. For example, when the electronic device (200) receives an input for selecting and saving a step on the self-diagnosis input UI (3270) illustrated in FIG. 8A, the electronic device (200) can display the side effect input UI (3310) illustrated in FIG. 8B. As an example, the electronic device (200) can display the side effect input UI (3310) at the user's request. The electronic device (200) can identify side effect keywords included in a database of medications and display them on the side effect input UI (3310). As an example, the database of medications can be included in an external device, and the electronic device (200) can receive side effect keywords from the external device. When the electronic device (200) receives an input to select and save at least one side effect on the side effect UI (3310), it can display the selected side effect information together with a visual object.

[0098] FIG. 9 is a diagram illustrating a UI of analysis data including side effect information according to various embodiments.

[0099] Referring to FIG. 9, a UI (3350) for drug analysis data is illustrated. For example, the UI for the analysis data may include a visual object area (3351) and a side effect information area (3353). The visual object area (3351) may include a first visual object including a first score according to a first factor and a second score according to a second factor before taking the drug, and a second visual object including a first score according to the first factor and a second score according to the second factor after taking the drug. For example, the side effect information area (3353) may include all side effect information received from the user. The electronic device (200) may display side effect information by distinguishing it according to the frequency and / or reception time of the received side effect information. For example, the electronic device (200) may distinguish side effect information by color, font size, font boldness, and / or shading. As an example, the electronic device (200) may display the most frequently received side effect information in the largest size. The electronic device (200) may display the most recently received side effect information in bold. For example, the electronic device (200) may assign weights to received side effect information based on frequency and reception time, display side effect information with the highest weight in red, and display side effect information in other colors according to the weight.

[0100] For example, the electronic device (200) may store biometric information related to the received side effect information. The electronic device (200) may continuously acquire biometric information periodically and / or at preset points in time. If the acquired biometric information is within a preset range of the biometric information related to the side effect information, the electronic device (200) may provide a notification to the user. For example, if the electronic device (200) receives side effect information such as feeling hot after taking medication, the electronic device (200) may acquire abnormal body temperature information at the time the side effect information is received. As another example, the electronic device (200) may confirm abnormal body temperature information from biometric information acquired after the time when the effect occurs after taking medication. For example, if the abnormal body temperature information is 37 degrees, the electronic device (200) may store abnormal body temperature information of 37 degrees in conjunction with the received side effect information such as feeling hot. The electronic device (200) may continuously acquire body temperature information periodically or at preset points in time. If the preset range is 0.2 degrees and the body temperature information obtained by the electronic device (200) is 36.8 degrees, the electronic device (200) can provide a notification to the user.

[0101] FIG. 10A and FIG. 10B are diagrams illustrating an operation of providing information on related drugs according to various embodiments.

[0102] Referring to FIG. 10A, a UI (3370) providing medication information related to a medication is illustrated. For example, the electronic device (200) may store a user's medication history and analysis data of the medication taken. The electronic device (200) may receive a user input requesting related information. Based on the stored medication history, the electronic device (200) may determine analysis data of other medications included in the same medication category as the medication being taken. For example, if the medication being taken is a sleeping pill, the same medication category may be a sleeping pill category. The electronic device (200) may generate and display visual objects based on the analysis data of other medications included in the same medication category, based on their effects and / or side effects. As an example, the electronic device (200) may determine the effect of another medication based on the area of ​​a visual object of the analysis data of other medications included in the same medication category. As an example, the electronic device (200) may determine the effectiveness of another drug based on at least one of a first score according to a first factor of the analysis data and / or a second score according to a second factor. As an example, the electronic device (200) may determine the effectiveness of another drug based on a weight set for the first factor and / or the second factor of the analysis data. The electronic device (200) may provide visual objects of a preset number of drugs with the best effectiveness. As an example, the electronic device (200) may provide visual objects of a preset number of drugs with the least number and / or frequency of side effects.

[0103] For example, the electronic device (200) may provide visual objects of other drugs, including a visual object of the medication being taken. For example, if the sleeping pill being taken is Qaa, and among the sleeping pills included in the same medication category, Qbb and Qcc are effective or have fewer side effects, the electronic device (200) may provide a visual object (3371) based on the analysis data of Qaa, a visual object (3372) based on the analysis data of Qbb, and a visual object (3373) based on the analysis data of Qcc. For example, the electronic device (200) may provide visual objects of other drugs, excluding the visual object of the medication being taken. For example, if the sleeping pill being taken is QQQ, and among the sleeping pills included in the same drug category, Qaa, Qbb, and Qcc are effective or have fewer side effects, the electronic device (200) can provide a visual object (3371) according to the analysis data of Qaa, a visual object (3372) according to the analysis data of Qbb, and a visual object (3373) according to the analysis data of Qcc.

[0104] The electronic device (200) may display an indicator (3376) recommending the drug with the best effect or the fewest side effects.

[0105] For example, the electronic device (200) can provide information on medications taken by others. As an example, the electronic device (200) can provide information on other medications based on the medication history and medication analysis data of registered family members. The electronic device (200) can connect to the family member's terminal device and / or external device and check the medication history and medication analysis data of the family member. The medication analysis data checked by the electronic device (200) may be analysis data of other medications included in the same medication category as the medication taken by the user. The electronic device (200) can generate and display visual objects based on the effects and / or side effects based on the family member's medication history and medication analysis data. The electronic device (200) can provide visual objects of a preset number of medications with the highest effects. As an example, the electronic device (200) can provide visual objects of a preset number of medications with the lowest number and / or frequency of side effects. The electronic device (200) may provide a visual object of at least one other medication on a UI (3370) providing medication information. The electronic device (200) may display an indicator (3376) recommending a medication with the best effect or the fewest side effects. As an example, the electronic device (200) may provide a visual object of the medication being taken and a visual object of another medication together on the UI (3370) providing medication information.

[0106] As an example, the electronic device (200) may provide information on other medications based on another person's medication history and medication analysis data that are greater than or equal to a preset correlation. As an example, the preset correlation may include a correlation between the overall biometric information of the user and the other person, a correlation between biometric information related to symptoms of the user and the other person, a correlation between the first and second factors of the user and the other person, and / or a correlation between the user and the other person's side effects that are greater than or equal to a preset value. The electronic device (200) may connect to an external device and check another person's medication history and medication analysis data that are greater than or equal to a preset correlation. The medication analysis data checked by the electronic device (200) may be analysis data of another medication included in the same medication category that includes the medication being taken by the user. The electronic device (200) may generate and display a visual object based on effects and / or side effects based on another person's medication history and medication analysis data that are greater than or equal to a preset correlation. The electronic device (200) may provide visual objects of a preset number of most effective medications. For example, the electronic device (200) may provide visual objects of a preset number of medications with the fewest number and / or frequency of side effects. The electronic device (200) may display visual objects of at least one other medication on a UI (3370) providing medication information. The electronic device (200) may display an indicator (3376) recommending the medication with the best effect or the fewest side effects.

[0107] For example, the electronic device (200) may provide information on medications included in a medication category based on symptoms input by the user based on effects and / or side effects using a learned artificial intelligence model. As an example, the artificial intelligence model may learn the medication history of the user, family members, and / or an unspecified number of others. As an example, the artificial intelligence model may learn analysis data of the user, family members, and / or an unspecified number of others. The medication information provided by the learned artificial intelligence model may be information on a single medication or information on a combination of multiple medications. As an example, if the combination of multiple medications includes a main medication and a sub-medication, the electronic device (200) may display the main medication and the sub-medication separately. As an example, the electronic device (200) may distinguish the main medication and the sub-medication by using different colors, line thicknesses, and / or sizes. As an example, the electronic device (200) may display the main medication in a large size or with a thick line.

[0108] Referring to FIG. 10B, a UI (3380) providing analysis data for different dosages is illustrated. The electronic device (200) may provide multiple visual objects of the same medication with different dosages. For example, the electronic device (200) may provide a first visual object (3381) for a 60 mg dose of Qaa, a second visual object (3382) for a 30 mg dose of Qaa, and a third visual object (3383) for a 120 mg dose of Qaa. The electronic device (200) may display an indicator (3386) recommending a medication with the best effect or the fewest side effects.

[0109] FIG. 11 is a diagram illustrating a UI for notifying a time of taking medication after receiving side effect information according to various embodiments.

[0110] Referring to FIG. 11, a medication reminder UI (3090) is illustrated. The electronic device (200) may provide a medication reminder to the user based on the entered medication schedule. For example, if the medication schedule for AAA medication is 1:30 PM, the electronic device (200) may provide a medication reminder for AAA medication at 1:30 PM. The electronic device (200) may display the medication reminder UI (3090) and output a notification sound and / or vibration.

[0111] After receiving side effect information, the electronic device (200) may provide a notification (3391) related to the side effect on the medication notification UI (3090). As an example, the electronic device (200) may provide a notification suggesting an inquiry to a doctor or pharmacist along with the received side effect information.

[0112] FIG. 12 is a diagram illustrating an operation of providing comparative data before and after taking a drug according to various embodiments.

[0113] Referring to FIG. 12, comparative data before and after taking the medication is illustrated. As an example, the electronic device (200) may provide a first type of UI (3410). As an example, the first type of UI (3410) may be a UI that includes brief information. Upon receiving a user input in the first type of UI (3410), the electronic device (200) may include a second type of UI (3430). As an example, the second type of UI (3430) may be a UI that includes specific information.

[0114] For example, if the medication is related to weight loss, the electronic device (200) may display comparative data including weight information before and after taking the medication. If the medication is related to insomnia, the electronic device (200) may display comparative data including deep sleep time before and after taking the medication. If the medication is related to blood pressure, the electronic device (200) may display comparative data including blood pressure information before and after taking the medication. If the medication is related to diabetes, the electronic device (200) may display comparative data including blood sugar information before and after taking the medication. If the medication is related to arrhythmia, the electronic device (200) may display comparative data including the degree of pulse regularity before and after taking the medication.

[0115] Figure 13 is a flowchart illustrating a method for providing information on medication according to various embodiments.

[0116] In the following examples, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0117] According to one embodiment, steps 1310 to 1360 may be understood to be performed in a processor (e.g., processor (230) of FIG. 2) of an electronic device (e.g., electronic device (200) of FIG. 2).

[0118] Referring to FIG. 13, the electronic device (200) may receive information about a drug based on a first input (e.g., a first user input) (1310). For example, the electronic device (200) may directly receive the name of the drug from the user and receive information about the drug based on the received name of the drug. When the electronic device (200) receives an input using a camera, the electronic device (200) may identify the name of the drug using the camera and receive information about the drug based on the identified name of the drug. The electronic device (200) may receive a prescription and receive information about the drug based on the received prescription. The electronic device (200) may obtain a drug category related to the drug based on the information about the drug (1320). For example, the electronic device (200) may obtain classification information about the drug from a database connected through an external device (e.g., a server) or may obtain a drug category based on the information about the drug. For example, the drug category may include a first drug category and a second drug category. The first drug category may be a drug category that includes analysis data that includes qualitative information (e.g., self-diagnosis information), and the second drug category may be a drug category that includes analysis data that includes quantitative information. For example, if the medication being taken is a pain reliever, the analysis data may include qualitative information, such as the degree of pain symptom relief, and thus the pain reliever-related drug may be classified into the first drug category. If the medication being taken is a weight loss-related drug, the analysis data may include weight loss information, and thus the weight loss-related drug may be classified into the second drug category. Drugs classified into the first and second drug categories may be further classified into sub-drug categories based on the type of drug and / or the corresponding symptom. For example, if the medication being taken is a headache medication, it may be classified into the first drug category and the headache medication or pain reliever categories.

[0119] The electronic device (200) may receive a second input (e.g., a second user input) indicating information on the time at which the medication was taken (1330). For example, the medication information may include a dosing schedule. The electronic device (200) may provide a dosing reminder to the user based on the dosing schedule. For example, the dosing reminder UI may include an entry for inputting whether or not to take the medication. The electronic device (200) may receive a dosing completion input (e.g., a second user input) from the user. For example, the electronic device (200) may directly receive a dosing completion input from the user that includes the time at which the medication was taken. For example, when the electronic device (200) receives a dosing completion input from the user, the electronic device (200) may determine the time information of the electronic device (200) as information on the time at which the medication was taken. The dosing completion input received from the user may indicate information on the time at which the medication was taken.

[0120] The electronic device (200) can acquire the user's biometric information (1340). For example, the electronic device (200) can continuously acquire biometric information periodically or at preset points in time. As an example, the preset points in time may include the time of taking medication or the time when the medication takes effect.

[0121] The electronic device (200) can obtain a first score based on a first factor and a second score based on a second factor (1350). For example, the first factor may include a factor commonly applied to multiple drug categories. As an example, the first factor may include activity information, sleep information, condition information, and / or calorie information. The first score based on the first factor may include a score that quantifies the first factor. For example, the second factor may include a factor applicable to a drug category related to the drug. As an example, the second factor may include weight information, blood sugar information, blood pressure information, heart rate information, sleep information, and / or self-diagnosis information. The second score based on the second factor may include a score that quantifies the second factor. The electronic device (200) can obtain a first score based on the first factor and a second score based on the second factor based on the obtained biometric information.

[0122] For example, if a drug is classified as a first drug category, the electronic device (200) can determine the time of onset of effect from the time of administration of the drug. The electronic device (200) can receive self-diagnosis information from the user after the determined time of onset of effect. For example, if the drug is a pain relief drug, the electronic device (200) can receive self-diagnosis information including the degree of pain relief and provide the received self-diagnosis information as a second factor.

[0123] For example, if the medication is related to weight loss, the electronic device (200) can determine the weight loss based on the user's biometric information. The electronic device (200) can provide weight information including the weight loss as a second factor. For example, if the medication is related to insomnia, the electronic device (200) can determine the deep sleep time based on the user's biometric information. The electronic device (200) can provide sleep information including the deep sleep time as a second factor.

[0124] The electronic device (200) may provide a first visual object (1360). The electronic device (200) may provide a visual object representing analysis data including a first score according to a first factor and a second score according to a second factor. For example, the visual object may include a chart, a treemap, a heatmap, an analysis table, a data sheet, a graph, and / or a histogram.

[0125] For example, if a medication is classified as a first medication category, the electronic device (200) may provide a visual object containing self-diagnosis information as a second factor. If the medication is related to weight loss, the electronic device (200) may provide a visual object containing weight information, including the weight loss, as a second factor. If the medication is related to insomnia, the electronic device (200) may provide a visual object containing sleep information, including the deep sleep time, as a second factor.

[0126] For example, the electronic device (200) may provide information on the medication taken and / or other medications related to the symptom. As an example, the electronic device (200) may determine analysis data of other medications included in a medication category including the medication based on the user's medication history. The electronic device (200) may generate and provide a visual object based on the effects and / or side effects from the analysis data of other medications. As an example, the electronic device (200) may provide analysis data of family members who have taken the medication and / or analysis data of others whose correlation is greater than or equal to a preset correlation as a visual object. As an example, the electronic device (200) may provide information on medications included in a medication category according to the symptoms input by the user based on the effects and / or side effects using analysis data of the medication learned by the artificial intelligence model.

[0127] As an example, an electronic device may include a display, at least one processor including a processing circuit, and a memory storing instructions. The instructions, when individually or collectively executed by the at least one processor, may be configured to cause the electronic device to receive information about a medication based on a first input. The instructions may be configured to cause the electronic device to obtain a medication category associated with the medication based on the information about the medication. The instructions may be configured to cause the electronic device to receive a second input indicating information about a time at which the medication was taken. The instructions may be configured to cause the electronic device to obtain biometric information of the user. The instructions may be configured to cause the electronic device to obtain a first score according to a first factor applied to a plurality of medication categories and a second score according to a second factor applied to the medication category associated with the medication based on the biometric information and the information about the time at which the medication was taken. The above instructions may be configured to cause the electronic device to provide, through the display, a first visual object representing the first score according to the first argument and the second score according to the second argument.

[0128] For example, the first factor may include at least one of activity information, sleep information, condition information, and calorie information. The second factor may include at least one of weight information, blood sugar information, blood pressure information, heart rate information, sleep information, and self-diagnosis information.

[0129] As an example, the instructions may be configured to cause the electronic device to determine an effect onset time from the time of taking the drug if the drug is classified into a first drug category, receive self-diagnosis information from the user if the effect onset time is satisfied, and provide a first visual object including the self-diagnosis information as the second factor.

[0130] As an example, the instructions may be configured to cause the electronic device to receive self-diagnosis information including a degree of pain symptom relief, if the drug category is related to pain relief, and to provide the self-diagnosis information with the second score according to the second factor.

[0131] As an example, the instructions may be configured to cause the electronic device to determine a weight loss based on the user's biometric information, if the drug category is related to weight loss, and to provide the weight information including the weight loss as the second score according to the second factor.

[0132] As an example, the instructions may be configured to cause the electronic device to determine a deep sleep time based on the user's biometric information, if the drug category is related to insomnia, and to provide the sleep information including the deep sleep time as the second factor.

[0133] As an example, the memory may store the user's previously taken medication history and analysis data of the previously taken medication. The instructions may be configured to cause the electronic device to receive an input indicating information on the time at which another medication was taken, determine analysis data of another medication included in the medication category including the medication based on the medication history according to additional inputs from the user, generate a second visual object based on at least one of an effect and a side effect from the analysis data of the other medication, and provide the second visual object through the display.

[0134] As an example, the instructions may be configured to cause the electronic device to provide at least one of analysis data of a family member who took the medication and analysis data of another person whose correlation is greater than a specified correlation as a third visual object.

[0135] As an example, the instructions may be configured to cause the electronic device to provide information on a drug included in a drug category according to a symptom input by the user based on at least one of an effect and a side effect using analysis data of the drug learned by the artificial intelligence model.

[0136] As an example, the instructions may be configured to cause the electronic device to receive information about side effects of the drug, store biometric information related to the side effects, periodically acquire biometric information of the user, and provide a notification to the user if the acquired biometric information of the user is within a specified range of the biometric information related to the side effects.

[0137] As an example, the instructions may be configured to cause the electronic device to obtain the most recently updated first score and second score based on the user's biometric information obtained at the time of the onset of effect of the administered medication or after the time of taking the medication.

[0138] As an example, the electronic device may include a smartphone. The instructions may be configured to cause the electronic device to obtain the biometric information from an external device.

[0139] As an example, the electronic device may include a wearable device. The instructions may be configured to cause the electronic device to provide data to an external device if a specified number of data including at least one of the first visual object, information related to the first factor, and information related to the second factor is greater than or equal to the specified number.

[0140] As an example, a method for providing information about a medication may include receiving information about the medication based on a first input. The method may perform an operation of obtaining a medication category associated with the medication based on the information about the medication. The method may include an operation of receiving a second input indicating information about a time at which the medication was taken. The method may include an operation of obtaining biometric information of a user. The method may include an operation of obtaining a first score according to a first factor applied to a plurality of medication categories and a second score according to a second factor applied to the medication category associated with the medication based on the biometric information and the information about the time at which the medication was taken. The method may include an operation of providing a first visual object representing the first score according to the first factor and the second score according to the second factor.

[0141] For example, the first factor may include at least one of activity information, sleep information, condition information, and calorie information. The second factor may include at least one of weight information, blood sugar information, blood pressure information, heart rate information, sleep information, and self-diagnosis information.

[0142] As an example, the method may further include an operation of determining the time of onset of effect from the time of administration of the drug if the drug is classified into the first drug category. The method may further include an operation of receiving the self-diagnosis information from the user if the time of onset of effect is satisfied. The operation of providing the first visual object may provide a first visual object including the self-diagnosis information as the second factor.

[0143] For example, the action of receiving the self-diagnosis information may receive the self-diagnosis information including the degree of pain relief if the drug category relates to pain relief. The action of providing the first visual object may provide the self-diagnosis information with the second score according to the second factor.

[0144] As an example, the method may further include an operation of determining the weight loss based on the user's biometric information, if the drug category relates to weight loss. The operation of providing the first visual object may provide weight information including the weight loss as the second score based on the second factor.

[0145] As an example, the method may further include an operation of determining the deep sleep duration based on the user's biometric information if the drug category is related to insomnia. The operation of providing the first visual object may provide the sleep information including the deep sleep duration as the second factor.

[0146] As an example, a non-transitory computer-readable storage medium having recorded thereon a program that performs a method for providing information on a medication may include an operation of receiving information on a medication based on a first input. The storage medium may include an operation of obtaining a drug category associated with the medication based on the information on the medication. The storage medium may include an operation of receiving a second input indicating information on a time at which the medication was taken. The storage medium may include an operation of obtaining biometric information of a user. The storage medium may include an operation of obtaining a first score according to a first factor applied to a plurality of drug categories and a second score according to a second factor applied to the drug category associated with the medication based on the biometric information and the information on the time at which the medication was taken. The storage medium may include an operation of providing a first visual object representing the first score according to the first factor and the second score according to the second factor.

[0147] The various embodiments of this document and the terminology used therein are not intended to limit the technical features described in this document to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the items, unless the context clearly indicates otherwise. In this document, each of the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" can include any one of the items listed together in the corresponding phrase among those phrases, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used merely to distinguish one component from another, and do not limit the components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as "coupled" or "connected" to another (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0148] The term "module" used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0149] Various embodiments of the present document may be implemented as software (e.g., a program (140)) including one or more instructions stored in a storage medium (e.g., an internal memory (136) or an external memory (138)) readable by a machine (e.g., an electronic device (101)). For example, a processor (e.g., a processor (120)) of the machine (e.g., an electronic device (101)) may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium.

[0150] According to one embodiment, the method according to various embodiments disclosed in this document may be provided as a computer program product. The computer program product may be traded between sellers and buyers as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or may be provided through an application store (e.g., Play Store). TM ) or directly between two user devices (e.g., smart phones), online distribution (e.g., downloading or uploading). In the case of online distribution, at least a portion of the computer program product may be at least temporarily stored or temporarily created in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0151] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separately arranged in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0152] The effects of this document are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the above description. While the present disclosure has been described and illustrated with reference to various embodiments, these embodiments may be illustrative rather than limiting. Those skilled in the art will readily appreciate that various changes in form and detail may be made without departing from the substantial spirit and full scope of the disclosure, including the appended claims and their equivalents. Furthermore, any of the embodiments described herein may be used in conjunction with other embodiments described herein.

Claims

1. In electronic devices, display; At least one processor comprising a processing circuit; and memory for storing instructions; The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: Receive information about the drug based on the first input, Based on the information about the above drug, a drug category related to the above drug is obtained, Receive a second input indicating information on the time at which the above medication was taken, Obtains the user's biometric information, Based on the above biometric information and the time information of taking the drug, a first score according to a first factor applied to multiple drug categories and a second score according to a second factor applied to the drug category related to the drug are obtained, An electronic device configured to provide a first visual object representing the first score according to the first factor and the second score according to the second factor through the display.

2. In paragraph 1, The first argument above is, Contains at least one of activity information, sleep information, condition information, and calorie information; The second argument is, An electronic device including at least one of weight information, blood sugar information, blood pressure information, heart rate information, sleep information, and self-diagnosis information.

3. In paragraph 2, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to determine the time of onset of effect from the time of taking the drug when the drug is classified into the first drug category, and to receive self-diagnosis information from the user when the time of onset of effect is satisfied, and to provide a first visual object including the self-diagnosis information as the second factor.

4. In paragraph 3, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to receive self-diagnosis information including the degree of pain symptom relief when the above drug category is related to pain relief, and to provide the self-diagnosis information with the second score according to the second factor.

5. In paragraph 2, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to determine the weight loss based on the user's biometric information when the above-mentioned drug category is related to weight loss, and to provide the weight information including the weight loss as the second score according to the second factor.

6. In paragraph 2, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to determine a deep sleep time based on the user's biometric information when the above drug category is related to insomnia, and to provide the sleep information including the deep sleep time as the second factor.

7. In paragraph 1, The above memory stores the user's previously taken medication history and analysis data of the previously taken medication, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to receive an input indicating information on the time at which another drug was taken, determine analysis data of the other drug included in the drug category including the drug based on the history of taking the drug according to additional inputs of the user, generate a second visual object based on at least one of an effect and a side effect from the analysis data of the other drug, and provide the second visual object through the display.

8. In paragraph 1, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to provide at least one of analysis data of a family member who has taken the above medication and analysis data of another person having a specific correlation or higher as a third visual object.

9. In paragraph 1, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to provide information on drugs included in a drug category based on symptoms entered by the user based on at least one of the effects and side effects, using drug analysis data learned by an artificial intelligence model.

10. In paragraph 1, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to receive information about side effects of the drug, store biometric information related to the side effects, periodically acquire biometric information of the user, and provide a notification to the user when the acquired biometric information of the user is within a specified range with the biometric information related to the side effects.

11. In paragraph 1, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device set to obtain the most recently updated first score and second score based on the user's biometric information obtained at the time of the onset of effect of the drug taken or after the time of taking the drug.

12. In paragraph 1, The electronic device includes a smartphone, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to obtain said biometric information from an external device.

13. In paragraph 1, The electronic device includes a wearable device, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: An electronic device configured to provide data to an external device when the data includes at least one of the first visual object, information related to the first factor, and information related to the second factor, if the number of data is greater than or equal to a specified number.

14. In the method of providing information on medication, An action of receiving information about a drug based on a first input; An action of obtaining a drug category related to the drug based on information about the drug; An action of receiving a second input indicating information on the time at which the above medication was taken; An action to obtain the user's biometric information; An operation of obtaining a first score according to a first factor applied to a plurality of drug categories based on the biometric information and the time information of taking the drug, and a second score according to a second factor applied to the drug category related to the drug; and A method comprising: providing a first visual object representing the first score according to the first argument and the second score according to the second argument.

15. In paragraph 14, The first argument above is, Contains at least one of activity information, sleep information, condition information, and calorie information; The second argument is, A method comprising at least one of weight information, blood sugar information, blood pressure information, heart rate information, sleep information, and self-diagnosis information.

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