Method and device for providing diagnosis result of nocturia disease in non-face-to-face manner

Abstract

The present disclosure relates to a method and device for providing a diagnosis result for nocturia diseases in a non-face-to-face manner. Provided according to an embodiment of the present disclosure is a method for providing a diagnosis result for nocturia disease in a non-face-to-face manner, the method comprising: performing a first test for determining the risk of developing a nocturia-related disease on the basis of basic health information of a user; performing a second test for diagnosing a nocturia disease if the first test result is normal; providing a diagnostic result, on the basis of results of the second test, for at least one of nocturnal polyuria (NP), lower urinary tract symptom (LUTS), overactive bladder (OAB), obstructive sleep apnea (OSA), and sleep disorders; and classifying treatment groups according to the severity of nocturia symptoms on the basis of the diagnostic results and basic health information.

Description

Method and device for providing diagnostic results for nocturia without face-to-face contact

[0001] The present disclosure relates to a method and device for providing diagnostic results for nocturia disease in a non-face-to-face manner.

[0002] Nocturia refers to urination during sleep, usually after waking up. Nocturia must be accompanied by sleep before or after urination, and is distinct from enuresis, which involves involuntary urination during sleep.

[0003] Nocturia is a common urinary disorder, affecting approximately 70% of people over 60 years of age. The number of patients with nocturia is increasing as the population ages.

[0004] According to the research results, nocturia reduces work productivity by 24% and leisure time activity by 34% compared to other chronic diseases, which shows that nocturia causes inconvenience in daily life and has a high incidence rate.

[0005] The main causes of nocturnal enuresis include nocturnal polyuria (NP), excessive urine output at night; sleep disorders that prevent deep sleep; and bladder dysfunction due to overactive bladder (OAB). Of these, nocturnal polyuria is the most common, affecting approximately 83% of nocturnal enuresis patients.

[0006] Treatment options for nocturia are broadly divided into behavioral therapy and pharmacological therapy. Behavioral therapy includes encouraging urination before bed and refraining from drinking water after dinner. Pharmacological therapy includes desmopressin, a synthetic analog of vasopressin.

[0007] Referring to the above, nocturia is a chronic condition that causes significant difficulties in daily life, and the number of people suffering from it is increasing. Therefore, there is a pressing need to develop a method that can diagnose nocturia remotely, without requiring an in-person visit, and suggest effective treatment options based on the results.

[0008] The present disclosure provides a method and device for providing diagnostic results for nocturia without face-to-face contact. The problems addressed by the present invention are not limited to those mentioned above. Other problems and advantages of the present invention, not mentioned above, can be understood through the following description and will be more clearly understood through the embodiments of the present invention. Furthermore, it will be appreciated that the problems and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims.

[0009] As a technical means for achieving the above-described technical task, a first aspect of the present disclosure is a method for providing a diagnosis result for nocturnal enuresis disease in a non-face-to-face manner, wherein a first test for determining the risk of developing a nocturnal enuresis-related disease is performed based on the user's basic health information, and when the result of the first test is normal, a second test for diagnosing nocturnal enuresis is performed, and based on the result of the second test, a diagnosis result for at least one of nocturnal polyuria (NP), lower urinary tract symptoms (LUTS), overactive bladder (OAB), obstructive sleep apnea (OSA), and sleep disorders is provided, and a treatment group can be classified according to the degree of symptoms of nocturnal enuresis based on at least one of the diagnosis result and the basic health information.

[0010] A second aspect of the present disclosure is a device for providing a diagnosis result for nocturia disease in a non-face-to-face manner, comprising: at least one memory; and at least one processor; wherein the at least one processor performs a first test for determining the risk of developing a nocturia-related disease based on the user's basic health information, and when the result of the first test is normal, performs a second test for diagnosing nocturia disease, and provides a diagnosis result for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder based on the result of the second test, and classifies a treatment group according to the degree of symptoms of nocturia disease based on at least one of the diagnosis result and the basic health information.

[0011] A third aspect of the present disclosure can provide a computer-readable recording medium having recorded thereon a program for executing the method according to the first aspect on a computer.

[0012] In addition, other methods for implementing the present invention, other systems, and computer-readable recording media storing a computer program for executing the method may be further provided.

[0013] Other aspects, features and advantages other than those described above will become apparent from the following drawings, claims and detailed description of the invention.

[0014] According to the problem solving means of the present disclosure described above, the present disclosure provides diagnosis results for nocturia disease in a non-face-to-face manner, thereby reducing the time required for a user to visit a hospital in person and receive a diagnosis of nocturia.

[0015] In addition, the present disclosure assesses the risk of multiple diseases related to nocturia before providing diagnostic results for nocturia and suggests in-patient treatment based on the results, thereby enabling users to prevent the onset of high-risk diseases in advance.

[0016] In addition, the present disclosure provides classification results into various treatment groups as diagnostic results for nocturia disease, thereby providing accurate diagnostic results.

[0017] In addition, the present disclosure can suggest an effective treatment direction for nocturia by suggesting different treatment methods for each treatment group of nocturia disease.

[0018] FIG. 1 is a conceptual diagram illustrating a method for providing diagnostic results for nocturia disease in a non-face-to-face manner according to one embodiment.

[0019] FIG. 2 is a block diagram of a device that provides diagnostic results for nocturia disease in a non-face-to-face manner according to one embodiment.

[0020] FIG. 3 is an exemplary configuration diagram of a system including a user terminal and an external device according to one embodiment.

[0021] FIG. 4 is a flowchart illustrating a method for providing diagnostic results for nocturia disease remotely according to one embodiment.

[0022] Figure 5 is a flowchart illustrating a method for classifying into detailed treatment groups according to the degree of symptoms of nocturia disease according to one embodiment.

[0023] FIG. 6 is a conceptual diagram illustrating a method for classifying the results of a first test into normal and abnormal according to one embodiment.

[0024] Figure 7 is a conceptual diagram illustrating a process for proposing in-patient treatment based on the results of the first examination according to one embodiment.

[0025] FIG. 8A is an exemplary diagram illustrating a third questionnaire for providing diagnostic results for sleep disorders included in a second examination according to one embodiment.

[0026] FIG. 8b is an exemplary diagram illustrating a third questionnaire for providing diagnostic results for sleep apnea included in a second examination according to one embodiment.

[0027] FIG. 9 is an exemplary drawing illustrating a fourth questionnaire included in a second test according to one embodiment.

[0028] FIG. 10 is an exemplary drawing illustrating a fifth questionnaire included in a second test according to one embodiment.

[0029] FIG. 11 is an exemplary drawing for explaining a urination diary according to one embodiment.

[0030] FIG. 12 is an exemplary diagram illustrating a method for determining a questionnaire to be included in a second examination based on basic health information of a user according to one embodiment.

[0031] Figure 13 is a conceptual diagram illustrating a process for proposing in-patient treatment based on the results of a second examination according to one embodiment.

[0032] FIG. 14 is an exemplary diagram illustrating a treatment group included in a first treatment group according to one embodiment.

[0033] FIG. 15 is an exemplary diagram illustrating a treatment group included in a second treatment group according to one embodiment.

[0034] One aspect of the present invention is a method for providing a diagnosis result for nocturnal enuresis disease remotely through a user terminal, the method comprising: performing a first test for determining the risk of developing a nocturnal enuresis-related disease based on the user's basic health information; performing a second test for diagnosing nocturnal enuresis disease when the result of the first test is normal; providing a diagnosis result for at least one of nocturnal polyuria (NP), lower urinary tract symptoms (LUTS), overactive bladder (OAB), obstructive sleep apnea (OSA), and sleep disorder based on the result of the second test; and classifying a treatment group according to the degree of symptoms of nocturnal enuresis disease based on at least one of the diagnosis result and the basic health information.

[0035] In addition, the basic health information may include at least one of information regarding the user's age, gender, height, weight, high blood pressure, diabetes, hyperlipidemia, unstable angina, myocardial infarction, heart failure, smoking, drinking, taking internal medicine medication, taking urology medication, and depression.

[0036] In addition, the method may further include a step of proposing an inpatient treatment for the treatment of the nocturia-related disease if the result of the first test is abnormal.

[0037] In addition, the above nocturia-related disease includes at least one of heart disease, menopause, endocrine disease, and mental disease, and the step of proposing the in-patient treatment may propose in-patient treatment in at least one of the departments of gynecology, cardiology, endocrinology, and psychiatry.

[0038] Additionally, information on whether or not the above depression is present can be obtained through a third test related to the depression scale.

[0039] In addition, the step of proposing the above-mentioned in-patient treatment may further include a step of obtaining the treatment results after the in-patient treatment and determining whether to perform the second examination.

[0040] Additionally, the second examination may include at least one of a first questionnaire regarding past medical history, a second questionnaire regarding the number of nocturia, a third questionnaire regarding sleep quality, a fourth questionnaire regarding overactive bladder, and a fifth questionnaire regarding prostate symptoms.

[0041] Additionally, the second test may include a voiding diary, and the voiding diary may include information on the amount of urine per day, the number of times urinating, and the number of times nocturia.

[0042] Additionally, the step of performing the second examination may further include a step of determining a questionnaire to be included in the second examination based on the basic health information.

[0043] In addition, the step of classifying the treatment group may further include a step of proposing an inpatient treatment in at least one of the departments of urology, sleep medicine, and internal medicine based on the results of the second examination.

[0044] Additionally, the step of classifying the treatment group may further include a step of classifying the treatment group based on the basic health information.

[0045] Additionally, the step of classifying the treatment group may further include a step of classifying the treatment group based on the results of the fourth test regarding motor ability.

[0046] Additionally, the step of providing the above diagnostic result may input the result of the second test into a neural network model to provide the above diagnostic result.

[0047] In addition, the step of classifying the treatment group may classify the treatment group by inputting at least one of the diagnosis result and the basic health information into a neural network model.

[0048] Another aspect of the present invention is a method for classifying treatment groups based on the degree of symptoms of nocturia disorder in a non-face-to-face manner through a user terminal, the method comprising: providing a diagnosis result for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder based on a test result for diagnosing nocturia disorder; first classifying the user into a treatment group included in a first treatment group based on the diagnosis result; second classifying the user into a treatment group included in a second treatment group based on basic health information of the user; and second classifying the user into a final treatment group based on the first classification result and the second classification result.

[0049] In addition, the first classification step may include a step of first classifying the user into a treatment group included in the first treatment group based on information on whether or not a drug related to nocturnal polyuria is prescribed, if the user is diagnosed with nocturnal polyuria.

[0050] In addition, the second classification step may include a second classification step into a treatment group included in the second treatment group based on the results of a test on driving ability.

[0051] In addition, the method may further include a step of presenting different treatment plans based on the determined final treatment group.

[0052] In addition, the above treatment plan may include at least one of a behavioral therapy plan, an exercise therapy plan, a side effect screening questionnaire plan for prescribed medication, and a proposal for in-patient treatment plan.

[0053] The advantages and features of the present invention, and the methods for achieving them, will become clearer with reference to the embodiments described in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments presented below, but may be implemented in various different forms, and it should be understood that it includes all transformations, equivalents, and substitutes included in the spirit and technical scope of the present invention. The embodiments presented below are provided to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention. In describing the present invention, if a detailed description of a related known technology is judged to obscure the gist of the present invention, the detailed description thereof will be omitted.

[0054] The terminology used in this application is only used to describe specific embodiments and is not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, it should be understood that the terms "comprise" or "have" indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but do not preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0055] Some embodiments of the present disclosure may be represented by functional block configurations and various processing steps. Some or all of these functional blocks may be implemented by various hardware and / or software configurations that perform specific functions. For example, the functional blocks of the present disclosure may be implemented by one or more microprocessors or by circuit configurations for a given function. Furthermore, for example, the functional blocks of the present disclosure may be implemented in various programming or scripting languages. The functional blocks may be implemented by algorithms that execute on one or more processors. Furthermore, the present disclosure may employ conventional techniques for electronic configuration, signal processing, and / or data processing. Terms such as "mechanism," "element," "means," and "configuration" may be used broadly and are not limited to mechanical and physical configurations.

[0056] Additionally, the connecting lines or connecting members between components depicted in the drawings are merely exemplary representations of functional connections and / or physical or circuit connections. In an actual device, connections between components may be represented by various functional connections, physical connections, or circuit connections that may be replaced or added.

[0057] The present disclosure will be described in detail with reference to the attached drawings below.

[0058] FIG. 1 is a conceptual diagram illustrating a method for providing diagnostic results for nocturia disease in a non-face-to-face manner according to one embodiment.

[0059] Referring to FIG. 1, the user terminal (30) can provide the user (10) with the diagnosis result (40) of nocturia and the corresponding treatment plan (50).

[0060] A user (10) can input basic health information (20) of the user (10) into a user terminal (30). Here, the basic health information (20) may include at least one of information regarding the user's (10) age, gender, height, weight, hypertension, diabetes, hyperlipidemia, unstable angina, myocardial infarction, heart failure, smoking, drinking, taking internal medicine medication, taking urology medication, and depression, but is not limited thereto.

[0061] The user terminal (30) can perform a first test to determine the risk of nocturia-related diseases other than nocturia based on basic health information (20) input from the user (10).

[0062] Nocturia can be accompanied by various medical conditions, as its incidence is high in older adults over 60 years of age. For example, conditions associated with nocturia can include, but are not limited to, diabetes, obesity, heart disease, and mental illness. Because these conditions can be more dangerous than the nocturia itself, it is necessary to suggest in-patient treatment for nocturia-related conditions before diagnosing the condition itself.

[0063] In the past, there was a problem in that diseases accompanying nocturia could not be filtered out in advance because the possibility of developing diseases related to nocturia was not considered in the diagnosis process for nocturia.

[0064] However, the user terminal (30) can filter out users (10) who may have diseases with a higher risk than nocturia by having the user (10) take the first test to determine the risk of developing a disease related to nocturia based on basic health information (20).

[0065] For example, the user terminal (30) may suggest to a user (10) whose first test result is abnormal to receive in-patient treatment without providing a diagnosis result (40) for nocturia.

[0066] In addition, the user terminal (30) can provide a diagnosis result (40) for nocturia by performing a test for nocturia on the user (10) after receiving an in-patient treatment. For example, the medical staff terminal can transmit the diagnosis result to the user terminal (30) after the in-patient treatment for the user (10) who has been suggested for an in-patient treatment. The user terminal (30) can decide whether to perform a test for nocturia on the user (10) based on the diagnosis result transmitted from the medical staff terminal. Through this, the user terminal (30) can perform an efficient nocturia diagnosis process by re-entering the user (10) who has been suggested for an in-patient treatment into the process of providing a diagnosis result (40) for nocturia.

[0067] In addition, the user terminal (30) may directly input the results of the in-patient treatment from the user (10) without receiving the results of the in-patient treatment from the medical staff terminal. Specifically, the user (10) may input the results of the in-patient treatment into the user terminal (30) after the in-patient treatment suggested by the user terminal (30). The user terminal (30) may determine whether to perform a test for nocturia on the user (10) based on the input results of the in-patient treatment.

[0068] Additionally, the user terminal (10) can perform a second test for diagnosing nocturia for a user (10) whose first test result is normal.

[0069] For example, the second examination may include, but is not limited to, at least one of a first questionnaire about past medical history, a second questionnaire about nocturia frequency, a third questionnaire about sleep quality, a fourth questionnaire about overactive bladder, a fifth questionnaire about prostate symptoms, and a voiding diary.

[0070] The user terminal (30) can provide the user (10) with a diagnosis result (40) for at least one of nocturnal polyuria (NP), lower urinary tract symptoms (LUTS), overactive bladder (OAB), obstructive sleep apnea (OSA), and sleep disorder based on the results of the second test.

[0071] In addition, the user terminal (30) can classify a treatment group according to the degree of symptoms of nocturia based on the diagnosis results (40) for nocturnal polyuria, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders.

[0072] Nocturnal polyuria, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders are the main causes of nocturia. The user terminal (30) can provide a final diagnosis result (40) of nocturia through the diagnosis result (40) of the main cause of nocturia and suggest a treatment plan (50) accordingly. Through this, the user terminal (30) can perform efficient treatment of nocturia by suggesting different treatment plans (50) depending on the cause of nocturia caused by various reasons.

[0073] For example, the user terminal (30) can determine the final treatment group for nocturia based on the first classification result classified based on the user's (10) basic health information (20) and the second classification result classified based on the user's (10) diagnosis results (40) for nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders.

[0074] FIG. 2 is a block diagram of a user terminal that provides diagnostic results for nocturia disease in a non-face-to-face manner according to one embodiment.

[0075] Referring to FIG. 2, the user terminal (100) includes a processor (110), a memory (120), and a communication module (130). In addition, the user terminal (100) may include a GPS module for determining the location of the user terminal (100).

[0076] For convenience of explanation, only components related to the present invention are illustrated in FIG. 2. Therefore, in addition to the components illustrated in FIG. 2, other general-purpose components may be further included in the user terminal (100). Furthermore, it will be apparent to those skilled in the art that the processor (110), memory (120), input / output interface (130), and communication module (140) illustrated in FIG. 2 may be implemented as independent devices.

[0077] Here, the user terminal (100) may be the same device as the user terminal (30) of FIG. 1.

[0078] The processor (110) can process computer program commands by performing basic arithmetic, logic, and input / output operations. Here, the commands can be provided from memory (120) or an external device. In addition, the processor (110) can generally control the operations of other components included in the user terminal (100).

[0079] For example, the processor (110) may perform a first test to determine the risk of developing a nocturia-related disease based on the user's basic health information. If the result of the first test is abnormal, the processor (110) may suggest an in-patient treatment for the nocturia-related disease. Furthermore, if the result of the first test is normal, the processor (110) may perform a second test to diagnose the nocturia-related disease. For example, the second test may include at least one of a first questionnaire regarding past medical history, a second questionnaire regarding the number of nocturias, a third questionnaire regarding sleep quality, a fourth questionnaire regarding overactive bladder, and a fifth questionnaire regarding prostate symptoms. For example, the processor (110) may determine the questionnaire included in the second test based on the user's basic health information.

[0080] Additionally, the processor (110) may provide a diagnostic result for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder based on the results of the second examination.

[0081] Additionally, the processor (110) can classify a treatment group according to the degree of symptoms of nocturia based on at least one of the diagnosis results for at least one of nocturnal polyuria, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders and at least one of the user's basic health information.

[0082] For example, the processor (110) may first classify a user based on a diagnosis of at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders. Additionally, the processor (110) may secondarily classify a user based on the user's basic health information.

[0083] Additionally, the processor (110) can determine a final treatment group for treating the user's nocturia diagnosis based on the first classification result and the second classification result.

[0084] For example, the user terminal (100) can provide a diagnosis result for nocturia using a neural network model. For example, the user terminal (100) can train the neural network model using the results of the first examination and the results of the second examination as input data for the neural network model and the diagnosis result for nocturia as output data. In addition, the user terminal (100) can obtain a diagnosis result for nocturia by inputting the results of the first examination and the results of the second examination into the trained neural network model.

[0085] In machine learning technology and cognitive science, a neural network model refers to a statistical learning algorithm implemented based on the structure of a biological neural network, or a structure that executes the algorithm.

[0086] For example, a neural network model can represent a model with problem-solving capabilities. Nodes, artificial neurons that form a network by combining synapses, similar to biological neural networks, repeatedly adjust the weights of synapses to learn to reduce the error between the correct output corresponding to a specific input and the inferred output. For example, a neural network model can include any probabilistic model used in artificial intelligence learning methods such as machine learning and deep learning, as well as neural network models.

[0087] For example, a neural network model can be implemented as a multilayer perceptron (MLP) composed of multiple layers of nodes and connections between them. The neural network model according to the present embodiment can be implemented using one of various artificial neural network model structures including MLP. For example, the neural network model can be composed of an input layer that receives an input signal or data from the outside, an output layer that outputs an output signal or data corresponding to the input data, and at least one hidden layer located between the input layer and the output layer that receives a signal from the input layer, extracts characteristics, and transmits the same to the output layer. The output layer receives a signal or data from the hidden layer and outputs it to the outside.

[0088] The processor (110) may be implemented as an array of a plurality of logic gates, or may be implemented as a combination of a general-purpose microprocessor and a memory storing a program that can be executed on the microprocessor. For example, the processor (110) may include a general-purpose processor, a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a controller, a microcontroller, a state machine, etc. In some environments, the processor (110) may include an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), etc. For example, the processor (110) may refer to a combination of processing devices, such as a combination of a digital signal processor (DSP) and a microprocessor, a combination of a plurality of microprocessors, a combination of one or more microprocessors coupled with a digital signal processor (DSP) core, or any other such combination of configurations.

[0089] The memory (120) may include any non-transitory computer-readable recording medium. For example, the memory (120) may include a non-permanent mass storage device such as a random access memory (RAM), a read only memory (ROM), a disk drive, a solid state drive (SSD), or a flash memory. As another example, the non-permanent mass storage device such as a ROM, an SSD, a flash memory, or a disk drive may be a separate permanent storage device distinct from the memory. In addition, the memory (210) may store an operating system (OS) and at least one program code (e.g., code for the processor (110) to perform the operations described below with reference to FIGS. 3 to 15). For example, the memory (120) may store basic health information of the user. In addition, the memory (120) may store information on treatment plans for each treatment group.

[0090] These software components may be loaded from a computer-readable recording medium separate from the memory (120). This separate computer-readable recording medium may be a recording medium that can be directly connected to the user terminal (100), and may include, for example, an input / output computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD / CD-ROM drive, a memory card, etc. Alternatively, the software components may be loaded into the memory (120) through a communication module (130) that is not a computer-readable recording medium. For example, at least one program may be loaded into the memory (120) based on a computer program (e.g., a computer program for the processor (110) to perform the operations described below with reference to FIGS. 3 to 15) that is installed by files provided by developers or a file distribution system that distributes installation files of applications through the communication module (130).

[0091] The input / output interface (130) may be a means for interfacing with a device (e.g., a keyboard, a mouse, etc.) for input and / or output that may be connected to or included in the user terminal (100). In FIG. 2, the input / output interface (130) is illustrated as an element configured separately from the processor (110), but is not limited thereto, and the input / output interface (130) may be configured to be included in the processor (110). For example, the processor (110) may derive the results of the first examination based on the user's basic health information input from the input / output interface (130).

[0092] The communication module (140) may provide a configuration or function for the user terminal (100) to communicate with an external device (not shown) via a network. In addition, the communication module (140) may provide a configuration or function for the user terminal (100) to communicate with another external device. For example, control signals, commands, data, etc. provided under the control of the processor (110) may be transmitted to an external device via the communication module (140) and the network.

[0093] FIG. 3 is an exemplary configuration diagram of a system including a user terminal and an external device according to one embodiment.

[0094] Referring to FIG. 3, the user terminal (310) may include any type of server that manages a web and / or app capable of providing artificial intelligence services. Furthermore, the user terminal (310) of FIG. 3 may be the same device as the user terminal (30) of FIG. 1 and / or the user terminal (100) of FIG. 2.

[0095] The external device (320) may include, but is not limited to, a server that manages a web service API capable of providing information. For example, the external device (320) may correspond to a medical staff terminal that transmits the user's visit treatment results to the user terminal (310).

[0096] For example, the user terminal (310) may determine whether to perform a second test for diagnosing nocturia based on the user's in-patient treatment results received from an external device (320). Through this, the user terminal (310) may re-enter the nocturia diagnosis process for the user who has been offered an in-patient treatment, thereby providing efficient diagnostic results.

[0097] The user terminal (310) and the external device (320) can communicate with each other and / or with other devices through a network. The network is a comprehensive data communication network that allows different entities to communicate smoothly with each other, and may include wired Internet, wireless Internet, and mobile wireless communication networks. For example, the network may include a local area network (LAN), a wide area network (WAN), a value-added network (VAN), a mobile radio communication network, a satellite communication network, and combinations thereof. In addition, wireless communication may include, but is not limited to, wireless LAN (Wi-Fi), Bluetooth, Bluetooth Low Energy, ZigBee, Wi-Fi Direct (WFD), ultrawideband (UWB), infrared communication (IrDA; Infrared Data Association), NFC (Near Field Communication), etc.

[0098] The user terminal (310) can communicate with an external device (320) via a network. By communicating via a network, the user terminal (310) can receive the user's medical examination results from the external device (320) and determine whether to perform a second examination.

[0099] FIG. 4 is a flowchart illustrating a method for providing diagnostic results for nocturia disease remotely according to one embodiment.

[0100] Referring to FIG. 4, a method for providing a diagnosis result for nocturia disease remotely is comprised of steps that are processed in a time-series manner in the user terminal (100) and / or processor (110) illustrated in FIG. 2. Therefore, even if omitted below, the content described above regarding the user terminal (100) or processor (110) illustrated in FIG. 2 can also be applied to the method for providing a diagnosis result for nocturia disease illustrated in FIG. 4.

[0101] In step 410, the user terminal can perform a first test to determine the risk of developing a nocturia-related disease based on the user's basic health information.

[0102] For example, basic health information may include, but is not limited to, at least one of the following: the user's age, gender, height, weight, high blood pressure, diabetes, hyperlipidemia, unstable angina, myocardial infarction, heart failure, smoking, drinking, taking internal medicine medication, taking urology medication, and depression.

[0103] For example, the first test may include, but is not limited to, at least one of the following: Test 1-1 to determine whether menopausal symptoms are present, Test 1-2 to determine whether heart disease is present, Test 1-3 to determine whether diabetes is present, Test 1-4 to determine whether urological medications are being taken, and Test 3 related to a depression scale.

[0104] For example, if the result of at least one of the tests 1-1 to 1-4 and the third test included in the first test is abnormal, the user terminal may determine the result of the first test as abnormal. Furthermore, if the results of all tests included in the first test are normal, the user terminal may determine the result of the first test as normal.

[0105] The method for determining whether each test included in the first test is normal or abnormal is described in detail in Figure 6 below.

[0106] In step 420, if the result of the first test is normal, the user terminal can perform a second test for diagnosing nocturia.

[0107] For example, the second examination may include at least one of a first questionnaire about past medical history, a second questionnaire about nocturia frequency, a third questionnaire about sleep quality, a fourth questionnaire about overactive bladder, a fifth questionnaire about prostate symptoms, and a voiding diary.

[0108] Additionally, the user terminal can determine which of the first to fourth questionnaires to include in the second examination based on the user's basic health information. For example, the user terminal can determine whether to include the fifth questionnaire in the second examination based on information about the user's gender contained in the user's basic health information. For example, if the user is female, the user terminal can exclude the fifth questionnaire from the second examination. Through this, the user terminal can provide efficient diagnostic results for nocturia.

[0109] In step 430, the user terminal may provide a diagnosis result for at least one of nocturnal polyuria, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder based on the results of the second test.

[0110] For example, the user terminal may provide a diagnostic result for nocturia based on the results of a second questionnaire on the frequency of nocturia and a voiding diary. Furthermore, the user terminal may provide a diagnostic result for sleep apnea and sleep disorders based on the results of a third questionnaire on sleep quality. Furthermore, the user terminal may provide a diagnostic result for overactive bladder based on the results of a fourth questionnaire on overactive bladder. Furthermore, the user terminal may provide a diagnostic result for lower urinary tract symptoms based on the results of a fifth questionnaire on prostate symptoms.

[0111] In one embodiment, the user terminal may provide the user with a diagnosis result for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders using a neural network model.

[0112] Specifically, the user terminal may input the results of the second test into a neural network model to provide the user with a diagnosis result for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders.

[0113] Additionally, the user terminal may train a neural network model to provide a diagnostic result for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders. For example, the user terminal may train a neural network model using the results of a second test performed on a previous nocturia patient as input data and using the diagnostic result for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders of the previous nocturia patient as output data.

[0114] In step 440, the user terminal can classify a treatment group according to the degree of symptoms of nocturia based on a diagnosis result for at least one of nocturnal polyuria, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder and at least one of the basic health information.

[0115] For example, the user terminal may determine whether to classify a treatment group according to the degree of symptoms of nocturia by additionally using the results of a fourth test on exercise capacity in addition to the diagnosis results for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder and basic health information.

[0116] Specifically, if the results of the fourth test are normal, the user terminal can classify the patient into a treatment group based on the severity of nocturia symptoms. Furthermore, if the results of the fourth test are abnormal, the user terminal can suggest a cardiologist's consultation without classifying the patient into a treatment group based on the severity of nocturia symptoms.

[0117] Additionally, if the user terminal determines that the user has high blood pressure based on the user's basic health information, the terminal can receive the results of a cardiology visit from the user. If the user terminal determines that the blood pressure is stable based on the cardiology visit results received from the user, the terminal can classify the user into a treatment group based on the severity of nocturia symptoms without performing a fourth test.

[0118] For example, the user terminal may first classify the user based on the diagnosis results for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders. Additionally, the user terminal may secondarily classify the user based on the user's basic health information.

[0119] Additionally, the user terminal can determine the user's final treatment group based on the first classification result and the second classification result.

[0120] In one embodiment, the user terminal may use a neural network model to determine a final treatment group for the user.

[0121] Specifically, the user terminal can input the diagnosis results and basic health information for at least one of nocturnal polyuria, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder into a neural network model to determine the final treatment group.

[0122] Additionally, the user terminal can train a neural network model to determine the final treatment group. For example, the user terminal can train a neural network model using the diagnosis results for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders of a previous nocturia patient as input data, and the final treatment group of the previous nocturia patient as output data.

[0123] In another embodiment, the user terminal may input the results of the second test and basic health information into a neural network model to determine the final treatment group.

[0124] Additionally, the user terminal can train a neural network model using the results of a second examination of a previous nocturia patient as input data and the final treatment group of a previous nocturia patient as output data.

[0125] Figure 5 is a flowchart illustrating a method for classifying into detailed treatment groups according to the degree of symptoms of nocturia disease according to one embodiment.

[0126] Referring to FIG. 5, the method for classifying into detailed treatment groups according to the degree of symptoms of nocturia is composed of steps that are processed in time series in the user terminal (100) and / or processor (110) illustrated in FIG. 2. Therefore, even if the content is omitted below, the content described above with respect to the user terminal (100) or processor (110) illustrated in FIG. 2 can also be applied to the method for classifying into detailed treatment groups according to the degree of symptoms of nocturia in FIG. 5.

[0127] In step 510, the user terminal may provide a diagnosis result for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder based on the test results for diagnosing nocturia disease.

[0128] Here, step 510 may be the same step as step 430 of FIG. 4.

[0129] In step 520, the user terminal may first classify the user into a treatment group included in the first treatment group based on the diagnosis result for at least one of nocturnal polyuria, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder.

[0130] For example, the first treatment group may include treatment groups 1-1 to 1-18 based on whether the user has nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorders.

[0131] In one embodiment, the user terminal may first classify the user into a treatment group included in the first treatment group using a neural network model.

[0132] Specifically, the user terminal can input the diagnosis results for at least one of nocturnal polyuria, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder into a neural network model to determine the first classification result.

[0133] Additionally, the user terminal may train a neural network model to determine the first classification result. For example, the user terminal may train a neural network model using the diagnosis results for at least one of nocturia, lower urinary tract symptoms, overactive bladder, sleep apnea, and sleep disorder of a previous nocturia patient as input data, and using the first classification result of the previous nocturia patient as output data.

[0134] The treatment groups included in the first treatment group are described in detail in Figure 14 below.

[0135] In step 530, the user terminal may secondarily classify the user into a treatment group included in the second treatment group based on the user's basic health information.

[0136] For example, a second treatment group may include treatment groups 2-1 through 2-8 based on whether the user is obese, diabetic, or has heart disease.

[0137] In one embodiment, the user terminal may use a neural network model to second-classify the user into a treatment group included in the second treatment group.

[0138] Specifically, the user terminal can input basic health information into a neural network model to determine a secondary classification result.

[0139] Additionally, the user terminal can train a neural network model to determine the secondary classification results. For example, the user terminal can train a neural network model using the basic health information of a previous nocturia patient as input data and the secondary classification results of the previous nocturia patient as output data.

[0140] The treatment groups included in the second treatment group are described in detail in Figure 15 below.

[0141] In step 540, the user terminal can determine the user's final treatment group based on the first classification result and the second classification result.

[0142] In one embodiment, the user terminal may use a neural network model to determine a final treatment group for the user.

[0143] Specifically, the user terminal can input the first classification result and the second classification result into a neural network model to determine the final treatment group.

[0144] Additionally, the user terminal can train a neural network model to determine the final treatment group. For example, the user terminal can train a neural network model using the first and second classification results of previous nocturia patients as input data, and the final treatment group of the previous nocturia patients as output data.

[0145] FIG. 6 is a conceptual diagram illustrating a method for classifying the results of a first test into normal and abnormal according to one embodiment.

[0146] Referring to FIG. 6, a user (610) can input basic health information (620) of the user (610) into a user terminal (630).

[0147] Additionally, the user terminal (630) can perform a first examination (640) based on the basic health information (620) of the input user (610).

[0148] For example, basic health information (620) may include at least one of information regarding the user's (610) age, gender, height, weight, high blood pressure, diabetes, hyperlipidemia, unstable angina, myocardial infarction, heart failure, smoking, drinking, taking internal medicine medication, taking urology medication, and depression, but is not limited thereto.

[0149] Additionally, the first test (640) may include, but is not limited to, at least one of the 1-1 test to determine whether menopausal symptoms exist, the 1-2 test to determine whether heart disease exists, the 1-3 test to determine whether diabetes exists, the 1-4 test to determine whether urological medication is being taken, and the 3rd test related to a depression scale.

[0150] For example, the user terminal (630) can determine the result of the 1-1 test based on the user's (610) age, gender, presence of facial flushing, presence of sweating, presence of insomnia, and presence of depression among the basic health information (620).

[0151] For example, the user terminal (630) may determine the result of the 1-1 test as abnormal if a woman aged 50 or older has at least two of the following symptoms: facial flushing, sweating, insomnia, and depression.

[0152] Additionally, the user terminal (630) can determine the results of the first and second tests based on whether the user (610) has at least three or more cardiovascular risk factors among the basic health information (620), unstable angina, myocardial infarction, heart failure, and vascular disease. Here, cardiovascular risk factors may include, but are not limited to, overweight, hypertension, diabetes, smoking, and hyperlipidemia. Additionally, vascular diseases may include, but are not limited to, cerebral infarction, peripheral vascular disease, myocardial disease, and heart valve disease.

[0153] For example, the user terminal (630) may determine the result of the first-second test as abnormal if the user (610) has at least three or more cardiovascular risk factors, has unstable angina, has a history of myocardial infarction, has heart failure, or has vascular disease.

[0154] Additionally, the user terminal (630) can determine the results of the first to third tests based on whether the user (610) has diabetes among the basic health information (620).

[0155] For example, the user terminal (630) may determine the results of the 1-3 tests as abnormal if the user (610) has diabetes and cannot control the diabetes through taking internal medicine.

[0156] Additionally, the user terminal (630) can determine the results of the 1-4 tests based on whether the user (610) is taking urological medication among the basic health information (620).

[0157] For example, the user terminal (630) may determine the results of the 1-4 tests as abnormal if the user (610) is taking Demopressin, a urological drug.

[0158] Additionally, the user terminal (630) can determine the result of the third test based on information on whether the user (610) has depression among the basic health information (620).

[0159] For example, if the result of the third test is greater than or equal to the first threshold, the user terminal (630) may determine the result of the third test as abnormal.

[0160] For example, the user terminal (630) may determine the result of the first test (640) as abnormal if the result of at least one of the tests 1-1 to 1-4 and the third test included in the first test (640) is abnormal. In addition, the user terminal (630) may determine the result of the first test (640) as normal if the results of all tests included in the first test (640) are normal.

[0161] For example, if the result of the first test (640) is normal, the user terminal (630) may perform a second test (660) related to nocturia. In addition, if the result of the first test (640) is abnormal, the user terminal (630) may suggest (650) an in-patient treatment to the user (610).

[0162] As an example, if the user terminal (630) determines that an in-patient treatment is necessary based on the results of the first examination (640) performed using basic health information (620), the user terminal may automatically perform procedures for an in-patient treatment.

[0163] For example, the user terminal (630) can determine the current location of the user terminal (630) and obtain information on hospitals located within a predetermined distance based on the current location. For example, if there is at least one hospital within a predetermined distance from the current location, the user terminal (630) can access the reservation system of that hospital and obtain information on available reservation times for a specific department for in-patient treatment. In addition, the user terminal (630) can display the searched hospital information and available reservation times.

[0164] Here, a specific medical department may include, but is not limited to, at least one of the following: gynecology, cardiology, endocrinology, urology, and psychiatry.

[0165] Additionally, the user terminal (630) can compare the user's schedule information stored in the user terminal (630) with the acquired reservable time information, and select and display a time suitable for the user.

[0166] Additionally, the user terminal (630) can access the reservation system of a hospital to which the user has visited based on the user's hospital visit history information and obtain a reservationable time.

[0167] Additionally, the user terminal (630) can search for hospitals close to the user's route based on the user's route information (e.g., the user's commuting route information, etc.) and obtain a time for which a reservation is available.

[0168] In another embodiment, when making a reservation for an in-patient treatment, the user terminal (630) may transmit information necessary for the in-patient treatment (e.g., EEG and electrocardiogram) to the relevant hospital. Furthermore, the user terminal (630) may obtain information from the hospital's reservation system regarding the availability of the information necessary for the aforementioned in-patient treatment.

[0169] In the past, in the diagnosis process of nocturia, only nocturia was diagnosed without considering the characteristic that nocturia is likely to be accompanied by related diseases such as menopause, diabetes, and heart disease.

[0170] However, the user terminal (630) can suggest (650) a priority visit to the user (610) for treatment of nocturia-related diseases, which have a higher risk than nocturia disease, by judging the risk before providing the diagnosis result of nocturia disease.

[0171] Figure 7 is a conceptual diagram illustrating a process for proposing in-patient treatment based on the results of the first examination according to one embodiment.

[0172] FIG. 7 is a conceptual diagram illustrating a process for proposing in-patient treatment based on the results of the first test (720) according to one embodiment.

[0173] Referring to FIG. 7, the user terminal (710) can perform a first examination (720) based on the user's basic health information. In addition, if the result of the first examination (720) is abnormal, the user terminal (710) can suggest (730) an in-patient treatment to the user.

[0174] For example, if the results of the first-first examination are abnormal, the user terminal (710) may suggest (740) gynecological examination. Furthermore, the user terminal (710) may receive the results of the gynecological examination from the medical staff terminal and determine whether to perform a second examination related to nocturia. For example, if the received examination results include a result indicating persistent nocturia, the user terminal (710) may decide to perform the second examination.

[0175] Additionally, the user terminal (710) can directly input the results of gynecological examinations from the user, without receiving the results from the medical staff terminal. Furthermore, the user terminal (710) can determine whether to perform a second examination based on the results of gynecological examinations input by the user.

[0176] Additionally, if the results of the first and second tests are abnormal, the user terminal (710) may suggest (750) cardiology treatment. Furthermore, the user terminal (710) may receive the results of the cardiology treatment from the medical staff terminal and determine whether to perform a second test related to nocturia. For example, if the received results indicate that the heart disease is controlled, the user terminal (710) may decide to perform the second test.

[0177] Additionally, the user terminal (710) can directly receive the results of cardiology treatment from the user, without receiving the results from the medical staff terminal. Furthermore, the user terminal (710) can determine whether to perform a second examination based on the results of cardiology treatment input by the user.

[0178] Additionally, if the results of tests 1-3 are abnormal, the user terminal (710) may suggest (760) an endocrinologist consultation. Furthermore, the user terminal (710) may receive the endocrinologist consultation results from the medical staff terminal and determine whether to perform a second examination related to nocturia. For example, if the received examination results include a result indicating that diabetes is under control, the user terminal (710) may decide to perform the second examination.

[0179] Additionally, the user terminal (710) may directly receive the endocrinology treatment results from the user, without receiving them from the medical staff terminal. Furthermore, the user terminal (710) may determine whether to perform a second examination based on the endocrinology treatment results input by the user.

[0180] Additionally, if the results of tests 1-4 are abnormal, the user terminal (710) may suggest (770) a urology consultation. Furthermore, the user terminal (710) may receive the results of a urology consultation from the medical staff terminal and determine whether to perform a second examination related to nocturia.

[0181] Additionally, the user terminal (710) may receive the results of urology treatment directly from the user, without receiving the results from the medical staff terminal. Furthermore, the user terminal (710) may determine whether to perform a second examination based on the results of the urology treatment input by the user.

[0182] Additionally, if the results of the third test are abnormal, the user terminal (710) may suggest (780) psychiatric treatment. Furthermore, the user terminal (710) may receive the results of the psychiatric treatment from the medical staff terminal and determine whether to perform a second test related to nocturia.

[0183] For example, the third test may correspond to the Center for Epidemiological Studies-Depression scale (CES-D). For example, if the result of the depression self-diagnosis test is higher than the first threshold, the user terminal (710) may suggest psychiatric treatment. In addition, if the result of the depression self-diagnosis test is higher than the second threshold but lower than the first threshold, the user terminal (710) may perform the third test again at predetermined intervals after treatment for nocturia begins.

[0184] In one embodiment, the user terminal may use a neural network model to determine whether to suggest an in-patient treatment to the user.

[0185] Specifically, the user terminal can input the results of the first test into a neural network model to determine whether to suggest an in-patient treatment to the user.

[0186] Additionally, the user terminal can train a neural network model. For example, the user terminal can train a neural network model using the results of a previous nocturia patient's first examination as input data and whether or not the patient was recommended for in-patient treatment as output data.

[0187] The user terminal (710) can efficiently provide diagnosis results by receiving the results of an in-patient examination and determining whether to re-perform the diagnosis process for nocturia.

[0188] FIG. 8A is an exemplary diagram illustrating a third questionnaire for providing diagnostic results for sleep disorders included in a second examination according to one embodiment.

[0189] FIG. 8b is an exemplary diagram illustrating a third questionnaire for providing diagnostic results for sleep apnea included in a second examination according to one embodiment.

[0190] Referring to FIG. 8a, image (810) corresponds to a third questionnaire for providing diagnostic results for sleep disorders included in the second examination.

[0191] Referring to FIG. 8b, image (820) corresponds to a third questionnaire for providing diagnostic results for sleep apnea included in the second examination.

[0192] For example, the user terminal may perform a second test for diagnosing nocturia. For example, the second test may include at least one of a first questionnaire regarding past medical history, a second questionnaire regarding the frequency of nocturia, a third questionnaire regarding sleep quality, a fourth questionnaire regarding overactive bladder, a fifth questionnaire regarding prostate symptoms, and a voiding diary.

[0193] For example, a first questionnaire regarding past medical history may include at least one of the following: a questionnaire regarding a history of mental illness, a questionnaire regarding a history of cerebrovascular disease and central nervous system disease, a questionnaire regarding a history of abdominal surgery and chemotherapy, and a questionnaire regarding a history of kidney and liver disease. For example, if the user has a history of at least one of the aforementioned diseases, the user terminal may suggest an in-patient visit.

[0194] Additionally, the second questionnaire regarding the frequency of nocturia may include, but is not limited to, at least one of the following: a questionnaire regarding age, a questionnaire regarding the number of times nocturia occurs per day, a questionnaire regarding quality of life (QoL) due to nocturia, a questionnaire regarding bedtime and sleep duration, and a questionnaire regarding difficulty falling asleep after nocturia.

[0195] For example, the user terminal may provide a diagnosis result for nocturnal polyuria based on the results of the second questionnaire. For example, if the analysis result of the second questionnaire of the user terminal indicates that the user is under 65 years of age and the amount of nocturnal urination out of the total amount of urination exceeds 20%, the user terminal may provide a diagnosis result indicating that the user has nocturnal polyuria. Additionally, if the user is over 65 years of age and the amount of nocturnal urination out of the total amount of urination exceeds 33%, the user terminal may provide a diagnosis result indicating that the user has nocturnal polyuria.

[0196] Additionally, referring to image (810), the third questionnaire on sleep quality may be, but is not limited to, the Insomnia Severity Scale (ISS) questionnaire to provide diagnostic results for sleep disorders.

[0197] For example, a third questionnaire may include seven questions related to insomnia. The user terminal may derive the results of the third questionnaire by summing the values ​​for each questionnaire. For example, if the results of the third questionnaire exceed a predetermined threshold, the user terminal may provide a diagnosis indicating that the user has a sleep disorder.

[0198] Additionally, referring to image (820), the third questionnaire on sleep quality may be, but is not limited to, a STOP BANG questionnaire to provide diagnostic results for sleep apnea.

[0199] For example, a third questionnaire may include eight questions related to sleep apnea. The user terminal can derive the results of the third questionnaire by summing the values ​​for each questionnaire. For example, if the results of the third questionnaire exceed a predetermined threshold, the user terminal can provide a diagnosis indicating that the user has sleep apnea.

[0200] FIG. 9 is an exemplary drawing illustrating a fourth questionnaire included in a second test according to one embodiment.

[0201] Referring to FIG. 9, image (900) corresponds to the fourth questionnaire on overactive bladder included in the second examination.

[0202] Referring to image (900), the fourth questionnaire for overactive bladder may be, but is not limited to, the Overactive Bladder Symptom Score (OABSS).

[0203] For example, the fourth questionnaire may include four questions to assess overactive bladder. The user terminal may derive the results of the fourth questionnaire by summing the values ​​for each questionnaire. For example, if the results of the fourth questionnaire exceed a predetermined threshold, the user terminal may provide a diagnostic result indicating that the user has overactive bladder.

[0204] FIG. 10 is an exemplary drawing illustrating a fifth questionnaire included in a second test according to one embodiment.

[0205] Referring to FIG. 10, image (1000) corresponds to the fifth questionnaire on prostate symptoms included in the second examination.

[0206] Referring to image (1000), the fifth questionnaire regarding prostate symptoms may correspond to, but is not limited to, the International Prostate Symptom Score (IPSS).

[0207] For example, the fifth questionnaire may include seven questions designed to assess lower urinary tract symptoms. The user terminal may derive the results of the fifth questionnaire by summing the values ​​for each questionnaire. For example, if the results of the fifth questionnaire exceed a predetermined threshold, the user terminal may provide a diagnosis indicating that the user has lower urinary tract symptoms.

[0208] FIG. 11 is an exemplary drawing for explaining a urination diary according to one embodiment.

[0209] Referring to FIG. 11, image (1100) corresponds to a urination diary included in the second examination.

[0210] Referring to image (1100), the user terminal can provide a diagnosis result for nocturnal polyuria based on the results of the voiding diary as well as the second questionnaire.

[0211] For example, a voiding diary may include information on the total number of times a day a person urinates (1110), the total amount of urine produced per day (1120), and whether or not a person urinates and the amount of urine produced during the night (1130).

[0212] For example, the user terminal may obtain information about the user's urine output every hour, but is not limited to this. The user terminal may obtain information about the user's urine output every 10 minutes.

[0213] For example, if the ratio of urine volume during the nighttime hours (1130) to the total daily urine volume (1120) (NPi; Nocturnal Polyuria index) is greater than a predetermined threshold, the user terminal may provide a diagnostic result indicating that the user has nocturnal polyuria. For example, if the value of NPi is 20% or greater, the user terminal may provide a diagnostic result indicating that the user has nocturnal polyuria.

[0214] FIG. 12 is an exemplary diagram illustrating a method for determining a questionnaire to be included in a second examination based on basic health information of a user according to one embodiment.

[0215] Referring to FIG. 12, table (1200) shows information about a questionnaire conducted based on the user's basic health information.

[0216] Referring to Table (1200), the user terminal can determine the questionnaire to be included in the second examination based on information about the user's gender included in the user's basic health information.

[0217] For example, if the user is male, the user terminal may not include the fourth questionnaire regarding overactive bladder in the second test. Furthermore, if the user is female, the user terminal may not include the fifth questionnaire regarding prostate symptoms in the second test.

[0218] Through this, the user terminal can reduce the time required to provide diagnosis results for nocturia by including only the questionnaires necessary for diagnosing nocturia in the second test, without including all questionnaires in the second test regardless of the user's basic health information.

[0219] Figure 13 is a conceptual diagram illustrating a process for proposing in-patient treatment based on the results of a second examination according to one embodiment.

[0220] Referring to FIG. 13, the user terminal (1310) can perform a second test (1320) for diagnosing nocturia.

[0221] Additionally, the user terminal (1310) can suggest an in-patient treatment (1330) based on the results of the second test (1320).

[0222] For example, the user terminal (1310) may suggest internal medicine treatment (1350) if the user has a history of mental illness, cerebrovascular disease, central nervous system disease, abdominal surgery, anticancer treatment, and kidney and liver disease, based on the results of the first questionnaire regarding past medical history.

[0223] Additionally, the user terminal (1310) may suggest sleep medicine treatment (1340) if the result of the third questionnaire on sleep quality is above a predetermined threshold.

[0224] Additionally, the user terminal (1310) may suggest urology treatment (1360) if the result of the fourth questionnaire on overactive bladder is above a predetermined threshold.

[0225] Additionally, the user terminal (1310) may suggest urology treatment (1360) if the result of the fifth questionnaire on prostate symptoms is above a predetermined threshold.

[0226] Additionally, the user terminal (1310) may suggest (1370) nephrology treatment if the total amount of urine per day has decreased by a predetermined threshold or more compared to the previous day among the results of the urination diary.

[0227] Through this, if the user terminal (1310) determines that the risk of a disease related to nocturia, such as sleep disorder, is high enough to provide a diagnosis result for nocturia in a non-face-to-face manner based on the results of the second test (1320), the user terminal can suggest an in-patient treatment to perform efficient treatment.

[0228] FIG. 14 is an exemplary diagram illustrating a treatment group included in a first treatment group according to one embodiment.

[0229] Referring to FIG. 14, table (1400) corresponds to a table showing the treatment groups included in the first treatment group.

[0230] For example, a user terminal can divide patients into treatment groups based on whether or not they experience nocturnal polyuria. Furthermore, for users diagnosed with nocturnal polyuria, the user terminal can divide patients into treatment groups based on whether or not they are prescribed medications related to nocturnal polyuria. For example, for users diagnosed with nocturnal polyuria, the user terminal can further divide patients into treatment groups based on whether or not they are prescribed Demopressin.

[0231] Additionally, the user terminal can divide the treatment group based on whether the user has lower urinary tract symptoms (LUTS) or overactive bladder (OAB). For example, if the user is male, the user terminal can divide the treatment group based on whether the user has LUTS. If the user is female, the user terminal can divide the treatment group based on whether the user has overactive bladder.

[0232] Additionally, the user terminal can divide the treatment group based on the presence of a sleep disorder or sleep apnea. For example, the user terminal can divide the treatment group based on the presence of a sleep disorder. Furthermore, for users with sleep disorders, the user terminal can divide the treatment group based on the presence of sleep apnea.

[0233] For example, the user terminal may include treatment groups 1-1 to 1-18 in the first treatment group based on the presence or absence of nocturnal polyuria, prescription of medication related to nocturnal polyuria, presence or absence of lower urinary tract symptoms or overactive bladder, presence or absence of sleep disorder, and presence or absence of sleep apnea.

[0234] FIG. 15 is an exemplary diagram illustrating a treatment group included in a second treatment group according to one embodiment.

[0235] Referring to FIG. 15, table (1500) corresponds to a table showing the treatment groups included in the second treatment group.

[0236] For example, a user terminal can be divided into treatment groups based on whether the user has diabetes. Furthermore, the user terminal can be divided into treatment groups based on whether the user has heart disease. Furthermore, the user terminal can be divided into treatment groups based on whether the user is obese.

[0237] For example, the user terminal may include treatment groups 2-1 to 2-8 in the second treatment group based on the presence or absence of diabetes, heart disease, and obesity described above.

[0238] For example, the user terminal can determine the user's final treatment group based on the first classification result into the first treatment group and the second classification result into the second treatment group.

[0239] For example, the user terminal can generate a total of 144 final treatment groups, including 18 treatment groups in the first treatment group and 8 treatment groups in the second treatment group. Furthermore, the user terminal can suggest different treatment options for each of the 144 final treatment groups.

[0240] Through this, the user terminal can perform effective treatment of nocturia by suggesting different treatment methods depending on the severity of the symptoms of nocturia.

[0241] Embodiments of the present invention may be implemented in the form of a computer program that can be executed through various components on a computer, and such a computer program may be recorded on a computer-readable medium. In this case, the medium may include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specifically configured to store and execute program instructions, such as ROMs, RAMs, and flash memories.

[0242] Meanwhile, the computer program may be specifically designed and constructed for the present invention, or may be one known and available to those skilled in the computer software field. Examples of computer programs may include not only machine language code, such as that generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like.

[0243] According to one embodiment, the method according to various embodiments of the present disclosure may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) through an application store (e.g., Play Store™) or directly between two user devices. In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0244] Unless the steps constituting the method according to the present invention are explicitly described in a specific order or are not described to the contrary, the steps may be performed in any appropriate order. The present invention is not necessarily limited to the order in which the steps are described. The use of all examples or exemplary terms (e.g., "for example," etc.) in the present invention is merely intended to illustrate the present invention in detail, and the scope of the present invention is not limited by the examples or exemplary terms unless otherwise defined by the claims. Furthermore, those skilled in the art will appreciate that various modifications, combinations, and variations can be configured according to design conditions and factors within the scope of the appended claims or their equivalents.

[0245] Therefore, the idea of ​​the present invention should not be limited to the embodiments described above, and all scopes equivalent to or equivalently modified from the following claims as well as the claims are considered to fall within the scope of the idea of ​​the present invention.

Claims

1. A method for providing diagnostic results for nocturia disease through a non-face-to-face user terminal, A step of performing a first test to determine the risk of developing a nocturia-related disease based on the user's basic health information; If the result of the first test is normal, a step of performing a second test for diagnosing nocturia; A step of providing a diagnosis result for at least one of nocturnal polyuria (NP), lower urinary tract symptoms (LUTS), overactive bladder (OAB), obstructive sleep apnea (OSA), and sleep disorders based on the results of the second test; and A step of classifying a treatment group according to the degree of symptoms of nocturia based on at least one of the above diagnostic results and the above basic health information; A method comprising:

2. In paragraph 1, The above basic health information is: A method comprising at least one of information regarding the user's age, sex, height, weight, whether the user has high blood pressure, diabetes, hyperlipidemia, unstable angina, myocardial infarction, heart failure, smoking, drinking, taking internal medicine medication, taking urology medication, and depression.

3. In paragraph 1, The above method, If the result of the first test is abnormal, a step of proposing an in-patient treatment for the treatment of the nocturia-related disease; A method comprising:

4. In paragraph 3, The above nocturia-related diseases are: Includes at least one of heart disease, menopause, endocrine disease, and mental illness; The steps for suggesting the above in-patient treatment are: A method of suggesting at least one outpatient treatment among gynecology, cardiology, endocrinology, and psychiatry.

5. In paragraph 2, Information on whether or not you have the above depression is as follows: Method obtained through a third test related to the depression scale.

6. In paragraph 3, The steps for suggesting the above in-patient treatment are: A step of obtaining the results of the examination after the above-mentioned visit to the hospital and deciding whether to perform the second examination; A method comprising:

7. In paragraph 1, The second test above is, A method comprising at least one of a first questionnaire regarding past medical history, a second questionnaire regarding the frequency of nocturia, a third questionnaire regarding sleep quality, a fourth questionnaire regarding overactive bladder, and a fifth questionnaire regarding prostate symptoms.

8. In paragraph 1, The second test above is, Include a voiding diary, The above urination diary is, A method comprising information on daily urine volume, frequency of urination, and frequency of nocturia.

9. In paragraph 7, The step of performing the above second inspection is: A step of determining a questionnaire to be included in the second examination based on the above basic health information; A method comprising:

10. In paragraph 1, The steps for classifying the above treatment groups are: A step of proposing an inpatient treatment in at least one of the departments of urology, sleep medicine, and internal medicine based on the results of the second examination; A method comprising:

11. In paragraph 1, The steps for classifying the above treatment groups are: A step of classifying the treatment group based on the above basic health information; A method comprising:

12. In paragraph 1, The steps for classifying the above treatment groups are: A step of classifying the treatment group based on the results of the fourth test on motor ability; A method comprising:

13. In paragraph 1, The step of providing the above diagnostic results is: A method for providing the diagnostic result by inputting the result of the second test into a neural network model.

14. In paragraph 1, The steps for classifying the above treatment groups are: A method for classifying a treatment group by inputting at least one of the above diagnosis results and the above basic health information into a neural network model.

15. A computer-readable recording medium recording a program for executing the method according to paragraph 1 on a computer.

16. At least one memory; and comprising at least one processor; At least one processor, A computing device that performs a first test to determine the risk of developing a nocturnal enuresis-related disease based on the user's basic health information, and if the result of the first test is normal, performs a second test to diagnose nocturnal enuresis, and provides a diagnosis result for at least one of nocturnal polyuria (NP), lower urinary tract symptoms (LUTS), overactive bladder (OAB), obstructive sleep apnea (OSA), and sleep disorder based on the result of the second test, and classifies a treatment group according to the degree of symptoms of nocturnal enuresis based on at least one of the diagnosis result and the basic health information.

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