110 results about "Patient management" patented technology

The invention discloses an oral diagnosis and treatment patient service platform based on reinforcement learning, and relates to the technical field of diagnosis and treatment services, and the platform comprises a health scoring module which integrates multi-source data, generates personalized oral health scores through a dynamic weight distribution model, and displays high-risk items in combination with 3D visualization; the patient management and marketing module tracks patient behaviors, clusters and classifies the patient behaviors, generates a dynamic follow-up visit path by using multi-target reinforcement learning, and matches a precise marketing verbal skill through a knowledge graph; the in-diagnosis auxiliary module synchronizes health data of the patient to the doctor terminal in real time, detects prescription conflicts and performs early warning, and generates personalized communication verbal skills in combination with historical preferences of the patient and real-time emotion analysis; through multi-dimensional data integration and intelligent processing, the whole oral diagnosis and treatment process is optimized, the diagnosis and treatment efficiency and the patient satisfaction degree are improved, the operation cost is reduced, and remarkable innovativeness and practicability are achieved.

The invention discloses a multi-modal data fusion-based intelligent management system for a thoracic surgery monitoring unit, belongs to the technical field of medical information and artificial intelligence, and aims to solve the limitation of an existing thoracic surgery monitoring system in the aspects of multi-modal data fusion, heterogeneous data semantic alignment and intelligent deep analysis and prediction decision. The system is characterized by comprising a multi-modal data acquisition unit, a heterogeneous data fusion and semantic alignment module, an intelligent analysis and prediction decision module, a man-machine interaction and visual presentation module and a secure storage and management module. By the adoption of the technical scheme, comprehensive multi-modal data fusion, high real-time performance, deep intelligent analysis and prospective prediction can be achieved, intelligent decision support, resource optimization, continuous learning and self-adaptive optimization are provided, and the intelligent level and patient management efficiency of the thoracic surgery intensive care unit are remarkably improved.

The invention provides a rectal cancer patient management method and system based on postoperative rehabilitation data analysis, and relates to the field of postoperative rehabilitation management. And executing cross-scene associated feature anomaly recognition to extract a sensitive feature variable set as observation input of the hidden Markov model, driving a rehabilitation stage transition probability to calculate and output a state anomaly feature combination, comparing and positioning a real-time rehabilitation state, calculating and outputting a dynamic rehabilitation stage switching time window, and sending the dynamic rehabilitation stage switching time window to a medical end screen display. The technical problems in the prior art that rehabilitation stage division is extensive, rehabilitation stage switching prediction precision of individual users is insufficient, and rehabilitation management suitability is affected are solved. The technical effects of eliminating the rehabilitation stage division lag effect, performing rehabilitation stage switching accurate prediction and providing high-reliability time sequence feature support for rehabilitation management are achieved.

The invention relates to the technical field of health assessment, and discloses a user climacteric physical and psychological health assessment and science popularization system, which comprises a science popularization plot and dynamic assessment process module, a multi-dimensional assessment engine and a general knowledge and personalized knowledge content push engine which are in closed-loop communication connection in sequence. According to the application, the science popularization garden and dynamic evaluation process module not only ensures data integrity, but also adapts to real-time updating requirements of medical guidelines; the multi-dimensional assessment engine fuses the multi-dimensional data and processes the medical scale, so that more comprehensive and accurate health assessment is realized; a general knowledge and personalized knowledge content pushing engine constructs a dynamic user portrait based on multi-dimensional data and evaluation results, and realizes accurate matching and interpretable pushing of health knowledge through a tag system and a four-dimensional evaluation system; the flexibility and the operation efficiency of the evaluation system and the acceptability of the user to the health management content are improved, and a finer and more efficient physical and psychological health doctor-patient management scheme is provided for climacteric people.

The invention relates to the technical field of patient management, and discloses a patient management method and system based on incubator traceability, and the method comprises the steps of information binding, data storage, expiration reminding and data verification. The system corresponds to the method. According to the application, the scanning device is utilized to realize accurate association of the incubator code and the patient identifier, and in combination with matching verification of the incubator function and the diagnosis and treatment stage, mistakes and omissions of manual binding are effectively avoided; equipment information, patient information and cleaning records are stored through an incubator database, multi-dimensional historical tracing query is supported, and full-life-cycle transparent management of an incubator use track and a cleaning process is achieved; a diagnosis and treatment association verification model is constructed, the accuracy of diagnosis and treatment data of a patient is intelligently verified based on multi-rule cross comparison such as spatial position, time logic and state change, and meanwhile, the early discovery capability of equipment abnormality and data contradiction is improved based on real-time monitoring of environmental parameters and linkage verification of physical sign data.

The invention relates to the technical field of health management, in particular to an obese patient remote dynamic intervention system based on AI early warning, which comprises a multi-dimensional data acquisition module, an AI risk layering and early warning module, a personalized intervention scheme generation module, a remote collaborative management module and an effect evaluation and optimization module, the multi-dimensional data acquisition module is used for acquiring patient related data; the AI risk layering and early warning module constructs a multi-dimensional dynamic score card model to carry out risk scoring and layering, and obesity health risk early warning is generated; a personalized intervention scheme generation module constructs a multidisciplinary intervention strategy matrix, and dynamically generates an intervention scheme according to an early warning result and individual features of a patient; the remote collaborative management module realizes information interaction and collaborative intervention of multi-party resources; and the effect evaluation and optimization module tracks the intervention effect and optimizes the model and the intervention scheme. Therefore, the problems of data lag, intervention scheme solidification, untimely early warning and the like in obese patient management are solved.

The invention discloses a postoperative sleep disorder key factor identification method, and belongs to the technical field of medical informatics, and the method comprises the steps: collecting data, and preprocessing the data into a candidate feature set; carrying out feature importance calculation by adopting evaluation methods of at least five different principles; the importance and stability of the features are evaluated through score and ranking analysis path fusion; the features are divided into four quadrants according to importance and stability indexes by using a two-dimensional scatter diagram, and feature classification is performed, so that key factors of the postoperative sleep disorder are accurately positioned. The method improves the robustness and consistency of feature evaluation through multi-model fusion, reduces the deviation of a single method, achieves the precise recognition of key factors of postoperative sleep disorders, supports the construction and intervention optimization of a clinical prediction model, and improves the diagnosis accuracy and patient management efficiency.

The invention relates to the technical field of medical treatment, in particular to a chronic infectious disease patient management system, which comprises a registration module used for registering identity information, body information, chronic infectious disease type information, chronic infectious disease condition information and other medical history information of a patient; the information database is used for storing disease condition characteristic data, historical treatment scheme data and precautions data of the chronic infectious diseases; the management platform comprises a doctor work station, a patient information station and a feedback module, and the doctor work station is used for obtaining cooperative information of a treatment scheme; the patient information station is used for generating a medicine taking scheme, a doctor seeing scheme and life precautions, and data of the patient information station is sent to the patient terminal, so that a patient obtains treatment and life related information; and the feedback module is used for inputting discomfort information of the patient. The treatment management efficiency of a hospital on the chronic infectious disease patient can be improved, and the chronic infectious disease patient can feed back own conditions in time.

1. The name of the design product: oral cavity detection report generation graphical user interface of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: the graphical user interface in the display screen panel. 4. The picture or photo that best shows the design points: front view. 5. The use of the graphical user interface: the interface is used to show the pages of the oral cavity detection report generation platform, the front view is the interface of logging into the oral cavity detection report generation platform and entering after clicking the "patient management" control; interface change state diagram 1 is the interface entered after clicking the control corresponding to the less than symbol in the right side of the front view; when the cursor is moved to the upper row of tooth icons in the two rows of tooth icons between the "tooth position map" label and the "image data" label in interface change state diagram 1, the tenth tooth icon from left to right, the interface shown in interface change state diagram 2 is displayed; interface change state diagram 3 is the interface entered after clicking any tooth icon between the "tooth position map" label and the "image data" label in interface change state diagram 2; interface change state diagram 4 is the interface entered after clicking any rectangular selection box below the "symptom overview" label in interface change state diagram 3; interface change state diagram 5 is the interface entered after clicking the gray block below the "image data" label in interface change state diagram 4. In each interface, the gray block represents a replaceable picture or oral three-dimensional model, and the symptom label is displayed around the oral three-dimensional model represented by the gray block. The front view reference diagram is the reference diagram of the front view, and the interface change state reference diagrams 1-5 are the reference diagrams of the interface change state diagrams 1-5.

The embodiment of the invention provides a hospitalized patient falling risk assessment method, device and equipment and a storage medium, the method is applied to the technical field of hospitalized patient management, and the method comprises the steps: obtaining multi-dimensional assessment information corresponding to a target patient; the multi-dimensional evaluation information comprises evaluation information corresponding to basic daily life activity information, evaluation information corresponding to fall risk evaluation scale information and evaluation information corresponding to a medical advice medication list; inputting the multi-dimensional assessment information into a risk assessment model for risk prediction, and obtaining a target risk prediction result; generating a target nursing scheme based on the target risk prediction result and the multi-dimensional evaluation information; and managing the target patient based on the target nursing scheme. According to the embodiment of the invention, the falling risk assessment efficiency of the inpatient can be improved, and the falling occurrence rate of the inpatient is reduced.

This invention relates to the fields of medical health and artificial intelligence technology, and particularly to a nasopharyngeal carcinoma patient management robot based on proactive health management and user profiling. It includes a main control module, a hardware layer, and a software functional layer. The hardware layer includes a screen interaction module, a voice interaction module, a data acquisition module, and a communication module for human-computer interaction, user data acquisition, and data communication. The software functional layer includes a user profile construction module, a multimodal emotion recognition module, an evidence-based response module, a multimodal temporal symptom proactive prediction module, a rehabilitation training module, and a diagnosis and treatment assistance module for nasopharyngeal carcinoma patient user profile construction, emotional interaction, evidence-based guidance, complication risk prediction, rehabilitation training, and diagnosis and treatment assistance. The storage module pre-stores a nasopharyngeal carcinoma-specific evidence-based knowledge base. This invention achieves precise symptom management for each nasopharyngeal carcinoma patient, completing a closed-loop management system encompassing multimodal empathic interaction, full-cycle coverage, data collection, analysis, intervention, and iteration.

The invention discloses a chronic obstructive pulmonary disease intelligent management system based on artificial intelligence, and the system comprises a doctor team module which is used for the login of a family doctor team and an operation system, and the doctor team module comprises a main interface and a menu bar; the patient management module is used for a patient and a guardian to log in and use the system, and the patient management module is divided into a patient login entrance and a guardian login entrance; and the AI cloud platform is used for storing, processing and pushing the health information of the patient, and the AI cloud platform is based on big data and strong deep learning ability thereof. According to the chronic obstructive pulmonary disease intelligent management system based on artificial intelligence, a doctor operation platform is comprehensive, a patient operation platform is simplified, family doctors are helped to provide chronic obstructive pulmonary disease health management, meanwhile, the acceptability of patients is improved, and the treatment compliance of the patients is improved through supervision of guardians.

The application provides an intestinal preparation quality real-time evaluation and whole-process management system based on artificial intelligence, which comprises the following functions: patient end provides intestinal preparation start time setting, laxative type selection, examination process and matters needing attention query and online consultation function; medical staff end provides patient management, progress and cleanliness score monitoring, early warning processing, data export and message interaction function, wherein the intelligent data acquisition module acquires multi-dimensional data; the artificial intelligence dynamic scoring module analyzes the data based on a deep learning model, generates a cleanliness pre-score and determines a quality grade; the active early warning and intervention module analyzes the data in real time, issues an early warning and provides intervention suggestions; the medical examination result closed-loop verification module receives the doctor's score after colonoscopy, compares and analyzes the pre-score, and optimizes the evaluation model. The application realizes the standardized guidance, active risk early warning and closed-loop optimization management of the intestinal preparation process, effectively improves the preparation quality, guarantees the safety of patients and optimizes the clinical decision-making.

Disclosed is a system that includes a computer-readable medium (CRM) coupling a variety of devices. The variety of devices can include one or more patient wearable sensor devices, a paired patient device, and a patient devices docking station. The system can also include a smart patient care cart, a nurse station, a lift tracker station, and / or an agnostic aggregation station. The system can also include a patient datastore, a facility datastore, a caregiver datastore, a device datastore, a patient state datastore, a patient management datastore, a facility management datastore, a caregiver management datastore, an electronic health record (EHR) system datastore, a health / fitness datastore, and an agnostic aggregation datastore.

The invention relates to the technical field of artificial intelligence, and provides a lesion risk prediction method, a lesion risk patient management system, equipment, a medium and a product, and the method comprises the steps: obtaining a risk depth feature, a risk interaction feature and an original risk feature; and inputting the risk depth feature, the risk interaction feature and the original risk feature into a lesion risk prediction model to obtain a risk prediction result of the histopathologic precancerous lesion. According to the lesion risk prediction method provided by the invention, on the basis of the practical situation that precancerous lesion samples are few, prediction comprehensiveness is enhanced through multi-feature cooperation, hidden deep features and risk interaction features in risk depth feature capture data reveal an inter-variable association mechanism, and original risk features reserve original basic data; the three are combined to break through single feature limitation, more comprehensive feature knowledge is added to the prediction model, the generalization ability and prediction precision of the prediction model are enhanced, and thus the risk prediction accuracy of cervical histopathologic precancerous lesions is improved.

The present disclosure discusses a urinary catheter attachment that is equipped with a sensor and microcontroller that monitors bladder parameters, such as pressure or volume, and determines when the bladder is full and should be voided. In various embodiment, the disclosed system allows individuals who cannot know, feel, or remember when their bladder should be voided to use catheter accessories such as catheter valves. According to various embodiments, the system computes bladder fullness through an algorithm and triggers the alert system when a bladder fullness threshold is passed. In various embodiments, the alert system includes, but is not limited to, notifications via smartphone or smart devices, wearable technology, and patient management systems. The alert system may be substituted with an electronically actuated catheter valve.

This disclosure is directed towards a patient management system for anticipating patient needs associated with toileting. In some examples, a computing device of the patient management system determines a toilet need schedule for a patient based on conditions of the patient (e.g., from an electronic medical record of the patient) and / or events that occur associated with the patient, such as meals or beverages consumed, toileting events, medications taken, and so forth. Additionally, the patient management system may sense when a patient is moving towards a patient relief device, when the patient is using the patient relief device, and / or when the patient has concluded using the patient relief device. Such information may be provided to a healthcare provider so that the healthcare provider may assist with toileting needs to increase safety of the patient and / or to reduce accidents associated with toileting needs of the patient.

The invention relates to the technical field of positioning systems, in particular to a patient management system suitable for an inpatient department, which comprises a plurality of wrist straps, a Bluetooth base station and a processing system, the processing system positions the patient according to the signal transmission parameters between the Bluetooth base station and the wrist strap to obtain a positioning result; patient hospitalization information is further pre-stored in the processing system, and the processing system predicts the action track of the patient according to the patient hospitalization information to obtain a predicted track; and the processing system corrects the positioning result according to the predicted trajectory. In order to solve the problem that a positioning scheme in the prior art is poor in positioning effect of a large number of densely carried terminals in an indoor scene of a department of inpatient, the scheme selects a Bluetooth positioning system to carry out adjacent positioning, an error compensation mechanism is constructed in combination with a movement track of a patient, and a relatively accurate positioning process is realized.

A patient management system and method for providing a risk profile and care plan to a patient and provider. The patient management system includes a risk analysis module configured to convert unstructured data to structured data and includes a data acquisition module for collecting and transmitting unstructured data and a classifier module for analyzing unstructured data and converting the unstructured data into structured data. The data acquisition module receives the unstructured data set, and the classifier module converts the unstructured data to a structured data set. A provider interface system is in communication with the classifier module and is configured to collect a plurality of structured data sets, analyze the collected structured data sets and output a risk profile / group to a provider.

The invention relates to a method for determining whether a subject diagnosed with a cardiovascular disease should be prescribed a remote patient management, the method comprising measuring particular biomarkers in a sample from said patient. The invention therefore relates to a method for therapy guidance, stratification and / or monitoring of a remote patient management for a patient diagnosed with a cardiovascular disease, comprising providing at least one sample of a patient, determining a level of at least one biomarker selected from the group consisting of proADM, proBNP and proANP or fragment(s) and comparing said level of the at least one biomarker to one or more reference values, wherein said level is indicative of prescribing or not prescribing a remote patient management for said patient. In some embodiments a low benefit level of the at least one biomarker is indicative of not prescribing a remote patient management, whereas in some embodiments a high benefit level of the at least one biomarker is indicative of prescribing a remote patient management. In some embodiments the cardiovascular disease is heart failure, in particular a chronic heart failure that has led to a hospitalization within the last 12 months.

The invention discloses a respiration monitoring method, a respiration monitoring system and respiration monitoring equipment for a post-anesthesia monitoring ward. The method comprises the following steps: acquiring voice data when a bed shifts, and acquiring image data of an electrocardiograph monitor in real time; recognizing the voice data to obtain basic information of the patient; the basic information of the patient at least comprises the name, gender, age, oxyhemoglobin saturation and medical history of the patient; segmenting and identifying the image data to obtain electrocardiogram monitoring data; the electrocardiograph monitoring data at least comprise QRS waves, respiratory waves, respiratory frequency values and blood pressure; inputting the basic information and the electrocardiograph monitoring data of the patient into the multi-source data prediction model to obtain a respiratory function prediction result; and judging the respiratory function prediction result based on a predefined medical decision to obtain a judgment result, and sending out a voice prompt or a corresponding alarm according to the judgment result. According to the invention, the respiratory function of the patient can be monitored in real time, the risk of adverse events is reduced, the medical work intensity is reduced, and the patient management quality is improved.

1. Name of this design product: Graphical user interface for an image management system for electronic equipment. 2. Purpose of this design product: for use in an electronic device. 3. The key design point of this design product lies in the graphical user interface content on the screen. 4. The picture or photo that best illustrates the key points of the design: main view. 5. Other views are of conventional design and are omitted. 6. Purpose of the graphical user interface: The interface of this design product is a graphical user interface of an image management system used for uploading, classifying, previewing and visual management of image data. 7. Human-computer interaction mode of the graphical user interface: the main view is the login interface of the image management system, and the interface usage status reference Figure 1 is the interface usage status reference diagram of the main view; in the main view, after entering the account and password, click the login button to enter the interface change status diagram 1, and the interface usage status reference Figure 2 is the interface usage status reference diagram of the interface change status diagram 1; the interface change status diagram 1 is the login interface after entering the salesperson's account and password, which can display the patient statistics of the current salesperson; in the interface change status diagram 1, click the patient management button in the left operation bar to enter the interface change status diagram 2, and the interface usage status reference Figure 3 is the interface usage status reference diagram of the interface change status diagram 2; the interface change status diagram 2 displays the information of all patients of the current salesperson; in the interface change status diagram 2, click the new patient button in the upper left corner of the right operation bar to enter the interface change status diagram 3, and the interface usage status reference Figure 4 is the interface usage status reference diagram of the interface change status diagram 3; the pop-up window of the interface change status diagram 3 displays the patient information that needs to be filled in; In interface change state diagram 3, after filling in the patient information in the pop-up window, click the OK button in the lower right corner of the pop-up window to enter interface change state diagram 4. Interface usage state reference diagram 5 is the interface usage state reference diagram of interface change state diagram 4; interface change state diagram 4 is the details page of the newly added patient, and the operation bar on the right includes the basic information area, the original image area, and the processing status area; in interface change state diagram 4, drag the image material to the original image area or click the original image upload button, and after selecting the image material, enter interface change state diagram 5, and interface usage state reference diagram 6 is the interface usage state reference diagram of interface change state diagram 5; interface change state diagram 5 shows the progress of uploading the image material and parsing and classifying the image material. When the progress is 100%, enter interface change state diagram 6; the image materials in interface change state diagram 6 are all under review, that is, waiting for review by the auditor on the management side; in interface change state diagram 6, click the preview button on the right side of the original image area to enter interface change state diagram 7; the pop-up window of interface change state diagram 7 displays the previewed image material.

Systems and methods are disclosed for improving posture detection to optimize medical device system resource allocation, including clustering received posture information occurring over a first time period into at least two clusters including a supine or upright cluster and at least one other cluster, determining, for each respective cluster, an opposite density measure indicative of a density of the posture information opposite the respective cluster in multi-dimensional space with respect to the posture sensor, identifying the supine or upright cluster using the opposite density measures of the at least two clusters, and determining the posture information for the patient using the identified supine or upright cluster.

The disclosed embodiments include a system and method for patient management using multi-dimensional analysis and computer vision. The system includes a base unit having a microprocessor connected to a camera and a beacon detector. The beacon detector scans for advertising beacons with a packet and publishes a packet to the microprocessor. The camera captures an image in a pixel array and publishes image data to the microprocessor. The microprocessor uses at least a Beacon ID from the packet to determine if an object is in a room, and Camera Object Coordinates from the image data to determine the coordinates of the object in the room.

The present invention provides a modular trochoidal drug pump device, a drive unit for the modular trochoidal drug pump device, a dosing set including the modular trochoidal drug pump device, and a drug delivery system having the modular trochoidal drug pump device and the drive unit thereof, thereby achieving high accuracy, user-friendly application, adaptability of application range, improved patient management and safety, and increased sustainability.

A system for managing liver disease, the system comprising an electronic medical record system comprising a plurality of patient records. The system comprising a patient management platform configured to access the electronic medical record (EMR) system to retrieve medical records of one or more patients, analyze the medical records to selectively identify data related to a liver condition, interface with one or more data analysis platforms configured to receive and analyze the data related to a liver condition. Based on analysis by the patient management interface and / or the data analysis platforms, a display is generated comprising: specific liver-related patient attributes and conditions, and at least one of: a liver health prognosis or a recommended treatment for addressing the liver condition corresponding to the one or more patients. The liver condition can comprise one or more of: cancer, cirrhosis, liver failure, fatty liver disease, steatosis, ischemia, and / or hepatitis.

1. The name of the design product: individual brain event-related brain function analysis graphical user interface of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: the content of the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 interface change state diagram 2. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the present graphical user interface is used for individual brain event-related brain function analysis. 7. The human-computer interaction mode of the graphical user interface: design 1 main view is a patient management interface, which can create a patient file and add a task; clicking icon A of design 1 main view enters design 1 interface change state diagram 1 to create an individual brain background, which shows the position of electrodes on the patient's brain, and the specific interface is shown in design 1 interface change state 1 reference diagram; clicking "next step" of design 1 interface change state diagram 1 enters design 1 interface change state diagram 2 to create a task-based brain function area positioning map, which characterizes the activation degree of electrode nodes by color. Design 2 main view is a patient management interface, which can create a patient file and add a task; clicking icon B of design 2 main view enters design 2 interface change state diagram 1 to create an individual brain background, which shows the position of electrodes on the patient's brain, and the specific interface is shown in design 2 interface change state 1 reference diagram; clicking "enter Mapping" of design 2 interface change state diagram 1 enters design 2 interface change state diagram 2, which can create and edit intraoperative and bedside functional electrical stimulation on the individual brain background.

1. The name of this design product: Tumor disease cohort graphical user interface for tablet computer. 2. Purpose of this design product: used to run the tumor disease cohort platform program, display and interact with information. 3. The key design point of this design product lies in the interface content of the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: Design 1 interface change state diagram 1. 5. Designate Design 1 as the base design. 6. Purpose of the graphical user interface: used for information management of patients with lung cancer, gastric cancer, and colorectal cancer, and for displaying information of patients with lung cancer, gastric cancer, and colorectal cancer. 7. Human-computer interaction method of the graphical user interface: In the enlarged diagram of the main interface of Design 1, the user enters the user name, password and verification code and clicks "Login" to enter the Design 1 interface change state diagram 1; in the Design 1 interface change state diagram 1, scroll the middle mouse wheel to enter the Design 1 interface change state diagram 2; in the Design 1 interface change state diagram 2, click "Patient Management" to enter the Design 1 interface change state diagram 3; in the Design 1 interface change state diagram 3, click "Enter" corresponding to the right of a patient to enter the Design 1 interface change state diagram 4. In the enlarged image of the main interface of Design 2, the user enters the user name, password and verification code and clicks "Login" to enter the Design 2 interface change state diagram 1; in the Design 2 interface change state diagram 1, scroll down the middle mouse wheel to enter the Design 2 interface change state diagram 2; in the Design 2 interface change state diagram 2, click "Patient Management" to enter the Design 2 interface change state diagram 3; in the Design 2 interface change state diagram 3, click "Enter" corresponding to the right side of a patient to enter the Design 2 interface change state diagram 4. In the enlarged image of the main interface of Design 3, the user enters the user name, password and verification code and clicks "Login" to enter the Design 3 interface change state diagram 1; in the Design 3 interface change state diagram 1, click "Patient Management" to enter the Design 3 interface change state diagram 2; in the Design 3 interface change state diagram 2, click "Enter" corresponding to the right side of a patient to enter the Design 3 interface change state diagram 3.