197 results about "Patient management" patented technology

The invention discloses a symptom management and prognosis evaluation method and system for a tumor radiotherapy patient, and relates to the technical field of tumor radiotherapy patient management.The method comprises the steps that basic information of the tumor radiotherapy patient is obtained, prognosis evaluation is conducted according to the basic information, a first result is generated, and the risk category is judged according to the first result; obtaining symptom information of a tumor radiotherapy patient, evaluating the symptom severity according to the symptom information, and generating a second result; and performing symptom management according to the second result and the risk category, generating prognosis data, and updating the first result through the prognosis data. According to the invention, by fusing the dual contrast learning network and the dual-path decision tree integrated model, the dynamic association analysis and adaptive feature enhancement of the multi-dimensional medical data of the tumor radiotherapy patient are realized, so that a precise prognosis evaluation and a personalized symptom management scheme are provided for clinical practice.

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 provides an intelligent critical patient multi-dimensional management system, and relates to the technical field of intelligent critical patient management. Comprising a data integration and cleaning module, a patient information management module, an algorithm and analysis module, a treatment scheme recommendation module and an early warning and intervention module, patient information can be mainly integrated through the data integration and cleaning module, and therefore previous treatment information of a patient can be rapidly detected. Advanced monitoring equipment and algorithms are integrated, the system can monitor vital signs of a patient in real time, early warning is immediately given out once abnormal data are detected, a quick response opportunity is provided for medical staff, the system not only monitors single vital signs such as the heart rate and the blood pressure, but also can comprehensively analyze multiple physiological parameters, and the medical staff can conveniently and quickly monitor the vital signs. Therefore, the health condition of the patient can be evaluated more comprehensively, and the trend change of data of the patient can be analyzed.

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 digital management platform for temporomandibular joint disorder, which relates to the field of medical health management and comprises a data acquisition module, a data processing module, a symptom evaluation and diagnosis module, a treatment scheme generation module, a patient interaction management module and a data visualization module. Multi-dimensional symptom data of a temporomandibular joint of a patient is collected in real time, the collected multi-dimensional symptom data is analyzed through data fusion, symptoms and signs of the patient are analyzed, a personalized diagnosis result is generated, a personalized treatment scheme is automatically recommended according to the diagnosis result of the patient, and the treatment progress is tracked. The system records the health record of the patient, provides remote medical support and interactive management functions, visually presents the symptom change, the treatment effect and the motion data of the patient to the patient and a doctor in the forms of charts and curves, and displays the change trend of the illness state of the patient along with time. According to the management platform, the diagnosis precision, the treatment effect and the patient management level of the TMD disease can be remarkably improved.

A patient management system can include an implantable neurostimulation device configured to deliver vagus nerve stimulation (VNS) therapy to a patient and a non-invasive, external monitoring device comprising at least one sensor for detecting indicators of seizure or depression in the patient. In an example, the external monitoring device is configured to use information from the at least one sensor to detect a seizure event or a seizure precursor event, audibly ask questions of the patient and / or provide behavioral modification commands to the patient, and / or control the neurostimulation device to deliver the VNS therapy to the patient in response to a detected seizure event, seizure precursor event, or progression of depression symptoms.

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 discloses a high-resolution breast cancer HER2 scoring method based on deep learning. The high-resolution breast cancer HER2 scoring method comprises the following steps: constructing a full-slide image data set containing hematoxylin-eosin and HER2 staining; accurately marking by a pathological expert, and distinguishing normal, in-situ and invasive tumor areas; cutting, classifying and marking blocks with different sizes and magnification times; carrying out gray level conversion, binarization and morphological operation on the image blocks to extract a tissue region; designing a deep learning model combining a visual converter and Fourier transform, and optimizing feature extraction and frequency domain analysis; an optimal backbone network structure is selected through comparison; the model is trained, parameters are optimized, and the recognition and evaluation accuracy is improved; and finally integrating to an automatic scoring software system to realize automatic identification, HER2 protein expression evaluation and automatic scoring. The system is high in automation degree, the HER2 scoring process is simplified, the auxiliary diagnosis precision is improved, the workload of doctors is reduced, and pathologists are helped to concentrate on complex diagnosis tasks, so that the patient management effect is improved.

The invention discloses a follow-up visit management system for an inflammatory bowel disease patient, and relates to the technical field of medical management. Comprising a patient management module which is in dynamic butt joint with a hospital information system, synchronizes patient data and endoscopic examination results in real time through an HL7 protocol, and establishes an electronic file containing an inflammatory bowel disease specificity tag; the diagnosis and treatment result module is used for storing structured data with temporal markers, including medication time sequences recorded by three groups of timestamps, administration routes and drug categories, auxiliary examination results accompanied with digestive tract pathological section images and hidden space feature vectors extracted from the images through a convolutional neural network; and the diet module is used for carrying out multi-level classification on diet photos uploaded by the patient through an image recognition unit based on MobileNetV3, and outputting food types and intake estimated values. According to the invention, by integrating the multi-dimensional data of the patient, the disease development trend is predicted, and personalized follow-up visit management is provided.

The invention discloses a digital medical science popularization and patient management coverage system and a solving method thereof, and belongs to the technical field of digital doctors, comprising a medical illness state database based on Internet of Things interaction, a key medical illness state data outline system customized according to the medical illness state database, and an AI large model GPT customization, creating a doctor-patient interaction AI illness state linguistic data model, and constructing a digital human medical knowledge display model. According to the invention, an AI illness state linguistic data model, an AI digital doctor image and a human body display model are established based on AI model customization software, so that the AI illness state linguistic data model and the AI digital doctor image and human body display model are used for the patients to answer the inquiry of medical questions and popular science of the corresponding questions, and the unified illness state linguistic data model and the digital human body medical knowledge display model are established through an AI technology. The system is used for forming different digital doctor models, and identifying, integrating and matching the doctor seeing information of a patient, so that a corresponding digital doctor can be quickly and effectively called out for explanation and science popularization according to a corresponding illness state.

The invention relates to the technical field of medical information, in particular to a clinical test patient screening and dynamic follow-up visit management method based on artificial intelligence, and the method comprises the following steps: collecting and standardizing admission, examination, medication and image data, mapping test items to form associated health data, comparing the group entering standard, screening qualified patients, and performing dynamic follow-up visit management. And extracting distribution mark difference crowds of medical units and patients, analyzing a physiological data fluctuation trend, and adjusting a follow-up visit sequence to generate a dynamic management plan. According to the method, by collecting structured health information and mapping test items, accurate screening and synchronous rhythm control are achieved, distribution of patients and medical units is analyzed, differential groups are recognized, resource allocation is optimized, a time sequence is constructed through physiological data, the difference value is calculated, and the health fluctuation trend is captured. The follow-up visit node is combined to adjust time arrangement, the execution efficiency is improved, and the patient management response speed and the data processing integrity are enhanced through multi-link cooperation.

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 discloses a chronic disease tracking management system, and belongs to the technical field of chronic disease patient management, and the system comprises a primary medical worker training module which is used for carrying out the skill and knowledge training of primary medical workers; the patient baseline data collection module is used for collecting patient baseline data and performing data analysis; the patient tracking guidance module is used for providing main control index monitoring guidance, daily nursing guidance, prevention control guidance, insulin injection guidance and the like for the patient; the prevention and improvement action plan module is used for monitoring health indexes of the patient, and regularly evaluating and timely adjusting a treatment scheme; analyzing and providing improvement suggestions according to the living habits of the patient; and the medical nutrition treatment module is used for formulating a personalized diet scheme with balanced nutrition for the patient. The system is intelligent, personalized and comprehensive, the chronic disease management level is integrally improved, and chronic disease prevention and treatment work is facilitated.

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 discloses a liver metastasis monitoring system based on big data, belongs to the technical field of medical treatment, and aims to solve the problems of high subjectivity, low accuracy and difficulty in meeting the requirements of clinical precision medical treatment when the clinical symptoms of a patient are pre-estimated, and the liver metastasis monitoring system comprises a data acquisition and integration module and a data preprocessing module, a liver metastasis risk prediction model construction module, a real-time risk assessment and early warning module and a decision assistance and suggestion module; through big data analysis and a machine learning algorithm, accurate prediction of the liver metastasis risk is realized, the diagnosis accuracy is improved, high-risk patients are found in time, accurate prediction and early warning of the liver metastasis risk of the patients are realized, and improvement of the early discovery rate and the treatment success rate of liver metastasis is facilitated; through an automatic processing flow, manual operation is reduced, unnecessary image examination is reduced, economic burden of a patient is reduced, doctor-patient contradiction is relieved, and patient management efficiency and service quality are improved.

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 present invention discloses a gastric cancer patient management system and method based on postoperative rehabilitation data analysis, which specifically relates to the field of postoperative rehabilitation management, and is used to solve the problem of delayed division of rehabilitation stages. The collected rehabilitation data is subjected to discrete wavelet transform, and noise filtering and missing value repair are implemented to ensure the integrity and continuity of the data, providing a high-quality data basis for subsequent analysis. The multi-order difference and local influence matrix are used to comprehensively evaluate the impact of interpolation points on the details of the original data, accurately capture the trend changes before and after the interpolation points, and effectively improve the reliability and accuracy of data repair. In addition, by correcting the similarity range between the patient's rehabilitation data sequence and the preset standard sequence, the ambiguity of the rehabilitation stage switching timing is eliminated, and the hidden Markov model is combined to analyze the state transition probability, accurately predict the switching timing of the rehabilitation stage, avoid the lag effect of stage division, and enable the rehabilitation plan to dynamically adapt to the actual needs of the patient.

To recommend inspection having high validity, according to a result at each timing of inspection, diagnosis, treatment and progress observation, in a whole workflow of a patient management.SOLUTION: A patient care plan determination system includes: a medical information server for holding attribute information and inspection results of a plurality of patients; an information terminal for providing a patient management policy indicating a classification of a target patient; and a calculator for acquiring predetermined information from the medical information server and the information terminal and determining a test item candidate related to a disease of the target patient. The calculator acquires the attribute information of the target patient and the patient management policy of the target patient from the medical information server, and applies patient attribute information of the target patient, a test result of the target patient, and the patient management policy of the target patient, to a test plan learned model for calculating a test value of each test item for specifying the disease according to the patient management policy, and executes estimation processing of a test value of a future test item candidate of the target patient and output processing of the test item candidate and the test value of the target patient.SELECTED DRAWING: Figure 1

The invention discloses a wounded person management system based on a medical care AI robot and an application method, and relates to the technical field of artificial intelligence first aid, and the system comprises a triage emergency rescue module which is used for collecting and preprocessing vital sign data, calculating a comprehensive health score based on the preprocessed vital sign data, and carrying out the classification and emergency rescue; and the hospital guide psychological rehabilitation module is used for carrying out hospital guide and treatment according to the classification result, collecting facial expression images of the wounded after treatment and calculating the emotion intensity. According to the invention, a triage emergency rescue module is used for collecting and preprocessing vital sign data, calculating a comprehensive health score and carrying out classification and emergency rescue; the hospital guide psychological rehabilitation module is used for conducting hospital guide and treatment according to the classification result, collecting facial expression images of the wounded after treatment and calculating the emotion intensity; the efficiency and accuracy of emergency treatment are improved, delay and misjudgment in the process of wounded person treatment are reduced, and personalized and accurate suggestions for wounded person treatment are enhanced.

Systems and methods are provided for remote patient management and monitoring. The patient is monitored with a wireless sensor system connected to an application executing on a patient user computing device. The system continuously monitors physiological parameters, such as, but not limited to, blood oxygen saturation (SpO2), pulse rate, perfusion index, pleth variability index, and / or respiration rate from the photoplethysmograph. The system triggers alarms if the patient physiological data violates thresholds. Care providers review patient data and associated alarm(s) with graphical user interfaces.

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 present invention is directed to a universal holder for safely supporting a number of anesthesia and critical care equipment in an organized manner on a single device. The universal holder includes a principal structure that includes an upper portion, a middle portion defining a notched channel, and a lower portion. A receiver plate is movably mounted and is vertically adjustable within the notched channel of the main plate. The receiver plate includes a structure for mounting pressure monitoring devices and manifolds. A removable transesophageal echocardiogram “TEE” probe mount is provided and is removably attachable to the receiver plate to secure the TEE probe to the universal holder. The universal holder includes a self-adjusting flexible hook to attach the universal holder to a bed handrail of a hospital bed and a foldable base plate to support the universal holder between a mattress and the frame of the hospital bed.

The invention relates to the technical field of medical information systems, and particularly discloses an early diagnosis data management system for a patient with schistosome hepatic fibrosis, which is used for acquiring blood biomarker data of the patient, and comparing and analyzing real-time blood biomarker data and historical blood biomarker data to obtain early diagnosis data of the patient with the schistosome hepatic fibrosis. Classifying the blood biomarker data into reliable data and unreliable data using a logistic regression model; calculating a variability deviation index and a logic deviation index of the blood biomarker data through a dynamic time warping and auto-encoder technology, and evaluating time stability and internal logic consistency of the blood biomarker data; performing normalization processing on the variability deviation index and the logic deviation index, and calculating an accuracy coefficient of the data; dividing the data into accurate data and inaccurate data according to the accuracy coefficient, and transmitting the accurate data to a patient management system.

The invention discloses a patrol service robot for a PET / CT waiting room, and the robot comprises a sensing and monitoring module which is used for monitoring the dynamic data of a patient and the environment in the waiting room in real time; the control system is used for planning a robot path according to the dynamic data and distributing task instructions; the mobile platform is used for enabling the robot to move to a designated position in the waiting room based on path planning; the interaction module is used for providing a man-machine interaction function and guiding the patient to complete preparatory work before examination; and the task execution module is used for executing the robot active intervention task based on the task instruction. Through multi-sensor fusion, intelligent control and man-machine interaction technologies, the problems of patient management, radiation protection, medical resource waste and the like are solved.

The invention belongs to the technical field of ward nursing, and provides a ward nursing alarm system comprising a physiological parameter monitoring module provided with a non-contact sensor; an artificial intelligence algorithm is built in the data analysis and processing unit; the alarm module adopts a multi-stage alarm mechanism; the environment monitoring and adjusting module is used for monitoring environment parameters in the ward; the patient behavior analysis module monitors the activity state of the patient through a camera and an action recognition algorithm; an integrated management platform; by integrating a plurality of modules such as a physiological parameter monitoring module, a data analysis and processing module, a multi-stage alarm module, an environment monitoring and adjusting module, a patient behavior analysis module and an integrated management module, continuous non-inductive monitoring of physiological parameters of a patient, intelligent identification and graded alarm of an abnormal state and automatic adjustment and monitoring of a ward environment are realized; and real-time monitoring and abnormal alarm of patient behaviors are realized, so that a convenient and efficient patient management and nursing means is provided for medical staff.

The invention provides a clinical auxiliary diagnosis method and system, computing equipment and a readable storage medium. The method comprises the following steps: acquiring an inquiry information result and medical record information of a target object; inputting the inquiry information result and the medical record information into a trained inquiry model to obtain an auxiliary diagnosis result; wherein the inquiry information result is obtained by the following steps: inputting the chief complaint information of the target object into a trained inquiry model to obtain inquiry information; and the target object answers the inquiry information to obtain an inquiry information result. The method can improve the diagnosis accuracy of doctors, reduce missed diagnosis and misdiagnosis, relieve the workload of the doctors and improve the medical efficiency. Meanwhile, a personalized treatment scheme is provided for the patient, patient management is optimized, and the treatment effect is improved. In addition, regional restrictions are broken through, high-quality medical resource sharing is achieved, and patients in remote areas can enjoy the same medical service as urban patients.

The invention relates to an intelligent internet bed reservation system, which comprises a diagnosis and treatment group intelligent management module for receiving disease characteristic data of a patient, generating a diagnosis and treatment group distribution scheme and outputting an operation schedule table to a dynamic scheduling engine; the dynamic scheduling engine module is used for generating time window prediction according to the operation scheduling table and starting a grading notification process; the notification and interaction module is used for generating patient customized notification content, feeding back a confirmation state to the patient management module and updating the hospitalization preparation progress; and the patient full-period management module is used for generating an electronic hospitalization certificate and optimizing a period prediction algorithm. According to the system, method and device for reserving the bed through the intelligent internet, the processor and the computer readable storage medium, the working efficiency of medical staff is improved, the patient receiving and treating plan is flexibly adjusted, and time is saved. The queuing condition can be checked at any time, and the patient can conveniently and reasonably arrange personal affairs.

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.

The invention, which relates to the technical field of clinic management business, discloses a clinic treatment auxiliary system comprising a medicine management module, a member management module, a patient management module, an outpatient service management module, a pharmacy management module, an execution management module, a reservation management module, an examination management module and a number calling large screen module. The medicine management module is used for counting according to the consumption state of each type of medicine; the member management module is used for managing member assets accumulated by the patient, such as points, recharge and balance, and associated family members enjoy common rights and interests; the patient management module is used for the system to automatically record files for each patient seeing a doctor in a clinic; the outpatient service management module comprises a patient file, doctor seeing information, doctor seeing information and a viewing report; the pharmacy management module is used for providing basic data, such as medicine names, specifications, usage and quantity information states, required by doctors during medicine preparation and also realizing online diagnosis and treatment and online medicine preparation functions; the execution management module is used for displaying patient archives and execution prescriptions; the appointment management module is used for enabling the patient to do not need to queue up and wait offline after online appointment time; the inspection management module displays the inspection analysis report according to the inspection; according to the clinic treatment assisting system, doctor-patient communication is facilitated, appointment and registration of the patient are facilitated, the queuing time for seeing a doctor is saved, and the efficiency is improved.