Intelligent assessment and diagnosis system for stress injury and application of intelligent assessment and diagnosis system in continuous nursing

Abstract

The invention relates to an intelligent assessment and diagnosis system for stress injury and application thereof in continuous nursing, based on implementation of the intelligent assessment and diagnosis system, a wound map of a patient with stress injury is intelligently identified and assessed through a built AI assessment model for stress injury, and corresponding staging and wound area of stress injury are output. And meanwhile, continuous nursing is carried out, corresponding continuous nursing propaganda and education data is intelligently decided for the pressure injury patient according to the staging and the area of the pressure injury, so that the staging and the size of the pressure injury can be quickly identified, and a chronic disease case management library of the pressure injury patient is established. Chronic disease resource sharing with doctors, patients and third parties is achieved, continuous management or whole-course management of chronic diseases is achieved, and nursing efficiency and clinical treatment accuracy of stress injuries are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of medical assessment technology, and in particular to an intelligent assessment and diagnosis system for pressure injuries and an application method and electronic equipment thereof in continuity care. Background Art

[0002] Pressure injury (PI) is listed as one of the five most common clinical complications in the 20th century and is also known as one of the most expensive complications in the 20th century. The incidence of pressure injury has always been high, ranging from 5.0% to 23.1% in foreign countries and up to 62.5% in my country. It not only brings negative effects such as pain, infection risk and increased medical expenses to patients, but also brings a heavy burden to society. In recent years, a lot of manpower and material resources have been invested in the treatment of pressure injuries, but the effect is not good.

[0003] The increasing in-depth research on pressure injuries by artificial intelligence has extended to the establishment of an information-based pressure injury protection system and an intelligent assessment and diagnosis system for hospitals. However, pressure injuries are a chronic disease, so the follow-up involves long-term care, which requires clinical nursing staff to accurately control the development of patients with pressure injuries and adjust nursing strategies in a timely manner.

[0004] However, in actual clinical nursing, the traditional and current methods of wound assessment and treatment of pressure injuries are highly dependent on personal knowledge and work experience, and the measurement results and treatment effects are uneven and lack continuity. Due to the influence of factors such as professional quality and experience, there are deficiencies and differences in the accuracy of pressure injury assessment by different nurses, and there are difficulties in the treatment and care of wounds.

[0005] In addition, the accuracy of wound image recognition in determining wound stage and size needs to be improved in China; there is a lack of replicable nursing methods that provide personalized operation pictures for nursing staff to refer to through image recognition; the use of information systems is limited to a certain hospital; there is a lack of continuity in continuing care for patients after discharge; and regional resources cannot be shared.

[0006] Therefore, how nurses can accurately and quickly assess the wound surface of pressure injuries, provide effective treatment and care based on the assessment results, and manage information sharing to reduce the harmfulness of pressure injuries is an urgent problem currently facing pressure injuries in clinical nursing. It is necessary to use intelligent recognition technology to improve the clinical nursing effect of pressure injuries. Summary of the invention

[0007] In order to solve the above problems, the present application proposes an intelligent assessment and diagnosis system for pressure injuries and an application method and electronic equipment thereof in continuity of care.

[0008] In one aspect, the present application provides an intelligent pressure injury assessment and diagnosis system, the system comprising:

[0009] Wound surface image acquisition system, used to collect wound surface images of patients with pressure injuries and send them to the cloud server;

[0010] A cloud server, configured to receive and process the wound surface image, intelligently evaluate the pressure injury stage of the pressure injury patient and calculate the corresponding wound surface area according to the wound surface image, and send the pressure injury stage and the wound surface area of ​​the pressure injury patient to a continuity care server;

[0011] A continuity care server, for intelligently making decisions on corresponding continuity care education data for patients with pressure injuries based on the location and stage of the pressure injury and the wound area;

[0012] The wound surface image acquisition system and the continuity care server are respectively communicatively connected to the cloud server.

[0013] As an optional implementation scheme of the present application, optionally, the cloud server includes:

[0014] A pressure injury AI assessment model, used to extract image features from the wound surface image and perform wound surface feature recognition, and output the recognized wound surface features;

[0015] A staging assessment module, for assessing and outputting the current pressure injury stage of the pressure injury patient according to the identified wound surface characteristics;

[0016] A wound surface contour extraction module, used for marking and extracting the wound surface contour of the wound surface feature on the wound surface image according to the expression characteristics of the wound surface feature on the wound surface image;

[0017] An area calculation module, used to calculate the area of ​​the wound surface contour to calculate the corresponding wound surface area;

[0018] The HIS system is used to record the pressure injury stage and the wound area of ​​the pressure injury patient and save them under the patient's consultation ID; and synchronously send each recorded pressure injury stage and wound area to the continuity care server.

[0019] As an optional implementation scheme of the present application, optionally, the method for generating the pressure injury AI assessment model includes:

[0020] Acquiring a training data set, wherein the training data set includes wound images at different pressure injury stages;

[0021] Performing feature engineering on wound images at different pressure injury stages in the training data set, extracting image features of wound images at different pressure injury stages, and constructing a corresponding wound image feature data set;

[0022] Based on a convolutional neural network, the image features of wound images at different pressure injury stages in the wound image feature data set are trained and learned to generate the pressure injury AI assessment model;

[0023] Randomly collect clinical wound images of patients with pressure injuries as a validation set, and use the validation set to evaluate and validate the pressure injury AI assessment model;

[0024] If qualified, the pressure injury AI assessment model is deployed on the cloud server to intelligently identify the image features of wound images of pressure injury patients at different pressure injury stages.

[0025] As an optional implementation scheme of the present application, optionally, the continuing care server includes:

[0026] A nursing education module, for automatically matching the continuity nursing education data corresponding to the pressure injury stage according to the pressure injury site and stage of the pressure injury patient;

[0027] A wound care annotation module, used to annotate the continuity care education data on the wound image of the pressure injury patient and generate a corresponding wound care guidance diagram;

[0028] The chronic disease management module is used to manage chronic diseases of patients with pressure injuries, including: recording and saving the pressure injury staging, wound area and wound care guidance chart of patients with pressure injuries at different stages.

[0029] As an optional implementation scheme of the present application, optionally, the chronic disease management module is also used for:

[0030] Sharing the wound care guidance diagram of each recorded pressure injury patient to the cloud server;

[0031] The cloud server is also used for:

[0032] The wound care guidance diagram of each recorded pressure injury patient is recorded in the HIS system and saved under the consultation ID of the pressure injury patient.

[0033] As an optional embodiment of the present application, optionally, the system further includes:

[0034] The EDA nursing terminal is used to request the cloud server to view the pressure injury clinical information of the pressure injury patient; and after the cloud server responds to the request, log in to the cloud server and enter the HIS system to view the first pressure injury clinical information of the corresponding pressure injury patient;

[0035] The patient end is used to log in to the cloud server and enter the HIS system to view the clinical information of the second pressure injury bound to the patient's medical ID;

[0036] a third-party backend server, configured to request the cloud server to share the pressure injury clinical information of the pressure injury patient; and, after the cloud server responds to the request, receive and view the third pressure injury clinical information of the corresponding pressure injury patient returned by the cloud server;

[0037] The first pressure injury clinical information, the second pressure injury clinical information and the third pressure injury clinical information include the following information:

[0038] The wound images of patients with pressure injuries at different stages and their corresponding wound features, the pressure injury staging, the wound area and / or the wound care guidance map.

[0039] On the other hand, the present application proposes an application method of the intelligent assessment and diagnosis system for pressure injuries in continuity care, which is implemented based on the intelligent assessment and diagnosis system for pressure injuries and includes the following steps:

[0040] The wound surface images of patients with pressure injuries are collected through the wound surface image acquisition system and sent to the cloud server;

[0041] The cloud server receives and processes the wound surface image, intelligently evaluates the pressure injury stage of the pressure injury patient and calculates the corresponding wound surface area according to the wound surface image, and sends the pressure injury stage and the wound surface area of ​​the pressure injury patient to the continuity care server;

[0042] The continuity care server intelligently determines corresponding continuity care education data for the pressure injury patient based on the pressure injury staging and the wound area.

[0043] In another aspect, the present application further provides an electronic device, comprising:

[0044] processor;

[0045] a memory for storing processor-executable instructions;

[0046] Wherein, the processor is configured to execute the application method.

[0047] Technical effects of the present invention:

[0048] Based on the implementation of the present invention, the present invention constructs an AI assessment model for pressure injury to intelligently identify and evaluate the wound images of patients with pressure injury, outputs the corresponding pressure injury stage and wound area, and simultaneously performs continuity care. According to the pressure injury stage, the corresponding continuity care education data is intelligently decided for the pressure injury patient, thereby being able to quickly identify the stage and size of the pressure injury, and by establishing a chronic disease case management database for patients with pressure injury, sharing of chronic disease resources between doctors, patients and third parties is achieved, continuity management or full-process management of chronic diseases is achieved, and the nursing efficiency and clinical treatment accuracy of pressure injuries are improved.

[0049] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0051] Figure 1 It is shown as a schematic diagram of the application system composition of the present invention;

[0052] Figure 2 Shown is a schematic diagram of the staged wound surface of the pressure injury of the present invention;

[0053] Figure 3 It is a schematic diagram showing the composition structure of the continuity care server of the present invention;

[0054] Figure 4 It is a schematic diagram showing the overall management composition of the application system of the present invention;

[0055] Figure 5 A schematic diagram showing nursing annotation of a patient's wound surface image according to the present invention is shown;

[0056] Figure 6 Shown is a schematic flow chart of the application method of the present invention;

[0057] Figure 7 It is a schematic diagram showing the application of the electronic device of the present invention. DETAILED DESCRIPTION

[0058] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0059] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0060] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present disclosure.

[0061] Example 1

[0062] like Figure 1 As shown, in one aspect, the present application provides an intelligent pressure injury assessment and diagnosis system, the system comprising:

[0063] Wound surface image acquisition system, used to collect wound surface images of patients with pressure injuries and send them to the cloud server;

[0064] A cloud server, configured to receive and process the wound surface image, intelligently evaluate the pressure injury stage of the pressure injury patient and calculate the corresponding wound surface area according to the wound surface image, and send the pressure injury stage and the wound surface area of ​​the pressure injury patient to a continuity care server;

[0065] A continuity care server, configured to intelligently make corresponding continuity care education data for pressure injury patients based on the pressure injury staging and the wound area;

[0066] The wound surface image acquisition system and the continuity care server are respectively communicatively connected to the cloud server.

[0067] The wound image acquisition system can be any type of device or system that can capture images of pressure injury wounds of patients with pressure injuries, such as an infrared camera or a cloud camera, etc. It can establish communication with a cloud server and report the acquired data to the cloud server.

[0068] This solution uses a cloud server to manage the wound surface of patients with pressure injuries. The pressure injury disease conditions of each patient can be recorded and tracked on the cloud server.

[0069] The patient's wound images can be intelligently evaluated on the cloud server, and the pressure injury AI assessment model deployed on the cloud server can be used to intelligently identify and output the patient's wound images collected in each assessment period, so as to quickly identify the patient's current pressure injury stage status and the corresponding wound area. Through intelligent recognition of wound images, the trauma features in the wound image can be identified, and the corresponding pressure injury stage can be identified based on the trauma features, and the patient's current possible stage of the trauma can be assessed. The follow-up nursing measures for the corresponding stage can be intelligently matched according to the stage, and the corresponding nursing education data can be configured for the patient's chronic disease management.

[0070] The system can automatically import and track the development of the patient's wound (wound caused by pressure injury) until it heals.

[0071] After wound feature recognition in each phase, the wound area can be calculated based on the wound features on the wound image, so as to judge the patient's wound healing condition based on the wound area calculated and evaluated in each phase.

[0072] The cloud server can be managed by a back-end administrator or a back-end service room, and can be implemented in conjunction with the back-end server of the existing hospital nurse station.

[0073] The continuity care server is dedicated to the chronic disease management services for patients. On this server, corresponding chronic disease nursing measures and education data are generated for chronic disease patients, as well as corresponding wound care guidance diagrams, which are used by nursing staff to conduct clinical assessments of patients and guide nursing staff to provide corresponding wound care for patients.

[0074] In this solution, the communication connection between each system and the server can refer to the configured hardware equipment, and the communication between the host where the cloud server is located and the continuity care server can be carried out in a manner similar to the intra-hospital communication mode.

[0075] The present invention obtains pressure injury wounds (for identifying staging and size) by constructing a model and quickly and accurately evaluating the photographed wounds. A trauma assessment AI model based on trauma data features is constructed based on deep learning technology. Note that the dimensions of the trauma training data set need to involve data such as wound area and staging. Combined with data feature engineering, data features are extracted and used for AI model training. It is necessary to construct continuity care measures corresponding to different evaluation results in the system to facilitate the intelligent AI model to quickly and accurately evaluate the photographed wounds. After obtaining the pressure injury wounds (staging and size), the corresponding trauma care measures are output in one step for continuity management.

[0076] The implementation principle of the present invention will be further described below.

[0077] As an optional implementation scheme of the present application, optionally, the cloud server includes:

[0078] A pressure injury AI assessment model, used to extract image features from the wound surface image and perform wound surface feature recognition, and output the recognized wound surface features;

[0079] A staging assessment module, for assessing and outputting the current pressure injury stage of the pressure injury patient according to the identified wound surface characteristics;

[0080] A wound surface contour extraction module, used for marking and extracting the wound surface contour of the wound surface feature on the wound surface image according to the expression characteristics of the wound surface feature on the wound surface image;

[0081] An area calculation module, used to calculate the area of ​​the wound surface contour to calculate the corresponding wound surface area;

[0082] The HIS system is used to record the pressure injury stage and the wound area of ​​the pressure injury patient and save them under the patient's consultation ID; and synchronously send each recorded pressure injury stage and wound area to the continuity care server.

[0083] The pressure injury AI assessment model is an AI model that is constructed by training and learning the wound images of several pressure injury patients through deep learning technology. The model can learn the wound image features of pressure injury patients at different stages.

[0084] like Figure 2 As shown, the wound surface image features of patients with pressure injuries at different stages can refer to the existing clinical staging images of various stages. It can also include wound surface images of deep tissue injuries (which can be prepared by the administrator).

[0085] For specific images of each stage, please refer to, for example, "Definition and Staging Interpretation of Pressure Injury by the National Pressure Ulcer Advisory Committee in 2016". Image features can be extracted based on convolutional neural networks, etc.

[0086] After the evaluation model is generated, it is clinically verified and deployed on a cloud server to perform intelligent image recognition and evaluation of wound images of chronic disease patients, especially those with pressure injuries, and intelligently output the patient's chronic disease staging status and the corresponding wound area. Therefore, it is possible to directly intelligently identify the wound image of the current patient, and intelligently output the corresponding wound staging status and the corresponding wound area, which is convenient for providing nurses with a clinical care foundation and facilitating subsequent accurate and continuous care for patients with pressure injuries. At the same time, manual evaluation by nurses is no longer required, which avoids subjective evaluation errors and improves clinical evaluation efficiency.

[0087] The staging assessment module can establish in advance the mapping relationship between wound surface features of different stages and corresponding analysis. After the AI ​​model identifies the wound surface features in the current wound surface image, the analysis and assessment module can automatically match the corresponding stage based on the wound surface features.

[0088] The model has learned the wound surface features corresponding to different stages, including the texture features, surface features, size, etc. that may appear in the wound surface in different stages. Therefore, the corresponding pressure injury stage can be matched by the wound surface features.

[0089] After obtaining the stage, the wound area is calculated.

[0090] In this solution, if the pressure injury AI assessment model is trained and learned for wound features of different stages and sizes, then when the model is subsequently used to intelligently identify and evaluate wound features on patient wound images, the corresponding stage and wound area can be directly matched based on the identified wound features.

[0091] In this solution, in order to further accurately calculate the wound area, a contour recognition algorithm is used. The parts showing wound characteristics on the wound image are marked with contours, and the area of ​​the marked wound contours is calculated to accurately calculate the wound area. In this solution, the wound contour extraction module can use OCR contour recognition algorithm, etc. to extract the contours of the areas showing wound characteristics on the wound image. Because the model has already identified the wound characteristics on the wound image, the area where the identified wound characteristics are located is marked with contours, and then the wound contour extraction module marks the marked contours, and then the area in the contours is calculated (generally, calculus is used to calculate irregular areas). The specific area calculation method used is not limited.

[0092] Therefore, the above solution can intelligently identify the patient's staging status and evaluate the corresponding wound area, which is also convenient for back-end nurses to provide further continuity care for patients. According to the wound characteristics, wound area, wound analysis, etc. identified and output by the cloud server, the corresponding continuity care measures can be accurately constructed.

[0093] In this solution, continuity care measures are mainly intelligently recommended by the continuity care server. According to the stage of the patient, the corresponding continuity care measures are recommended. Therefore, on the subsequent continuity care server, the continuity care measures and education measures corresponding to different stages are also constructed. When the continuity care server receives the information such as the current stage of the patient and the characteristics of the wound surface fed back by the original server, the continuity care server can automatically match the corresponding continuity care measures and education data to realize the intelligent and information-based chronic disease management of patients with pressure injuries.

[0094] As an optional implementation scheme of the present application, optionally, the method for generating the pressure injury AI assessment model includes:

[0095] Acquiring a training data set, wherein the training data set includes wound images at different pressure injury stages;

[0096] Performing feature engineering on wound images at different pressure injury stages in the training data set, extracting image features of wound images at different pressure injury stages, and constructing a corresponding wound image feature data set;

[0097] Based on a convolutional neural network, the image features of wound images at different pressure injury stages in the wound image feature data set are trained and learned to generate the pressure injury AI assessment model;

[0098] Randomly collect clinical wound images of patients with pressure injuries as a validation set, and use the validation set to evaluate and validate the pressure injury AI assessment model;

[0099] If qualified, the pressure injury AI assessment model is deployed on the cloud server to intelligently identify the image features of wound images of pressure injury patients at different pressure injury stages.

[0100] The steps of using convolutional neural networks (CNNs) to extract image features and generate AI models can usually be summarized into the following key stages:

[0101] 1. Data preprocessing

[0102] Data format conversion: Ensure that the image data exists in a format suitable for convolutional neural network processing, such as JPEG, PNG, etc.

[0103] Normalization: Convert pixel values ​​to between 0 and 1 for easier network processing.

[0104] Data augmentation (optional): Increase the diversity and robustness of the data through random cropping, rotation, flipping, etc.

[0105] 2. Build a convolutional neural network model

[0106] Select model architecture: Select a suitable convolutional neural network model and determine parameters such as the number of layers and convolution kernel size.

[0107] Initialize weights and biases: Initialize the weights and biases in the model so that they can be optimized during training.

[0108] 3. Set model details

[0109] Activation function: An activation function, such as ReLU, is used after each convolutional layer to enhance the nonlinear modeling capability of the model.

[0110] Pooling or downsampling: Depending on the task requirements, perform pooling operations, such as maximum pooling, at appropriate locations to reduce computational complexity and extract more representative features.

[0111] Output layer design: Determine the output layer structure according to the task type. For example, for a classification task, the output layer may be a softmax layer.

[0112] 4. Model training and optimization

[0113] Divide the data set: Divide the original data set into a training set, a validation set, and a test set (randomly collected clinical wound images used in this scheme), usually in a ratio of 7:2:1.

[0114] Define the optimizer: Choose a suitable optimizer, such as Stochastic Gradient Descent (SGD) or Adam, and set the learning rate accordingly.

[0115] Loss function: Select an appropriate loss function based on the task, such as the cross entropy loss function for classification tasks.

[0116] Training process: Use the training set to train the model, use the validation set to evaluate the model performance, and adjust parameters and optimize based on the evaluation results.

[0117] 5. Feature extraction and model generation

[0118] Feature extraction: Extract high-level features of the image through the trained convolutional neural network model.

[0119] Model generation: Generate corresponding AI models, such as classifiers and regressors, based on the extracted features and task requirements.

[0120] 6. Model Evaluation and Deployment

[0121] Model evaluation: Use the test set to evaluate the trained model and verify its performance in the actual task.

[0122] Model deployment: Deploy the trained model to actual applications to realize the functions of image feature extraction and AI model generation.

[0123] This solution also uses the above-mentioned CNN to train and generate the pressure injury AI assessment model. Please implement and understand it in combination with the above-mentioned principles.

[0124] like Figure 3 As shown, as an optional implementation scheme of the present application, optionally, the continuity care server includes:

[0125] A nursing education module, for automatically matching the continuity nursing education data corresponding to the pressure injury stage of the pressure injury patient according to the pressure injury stage of the pressure injury patient;

[0126] A wound care annotation module, used to annotate the continuity care education data on the wound image of the pressure injury patient and generate a corresponding wound care guidance diagram;

[0127] The chronic disease management module is used to manage chronic diseases of patients with pressure injuries, including: recording and saving the pressure injury staging, wound area and wound care guidance chart of patients with pressure injuries at different stages.

[0128] The continuity care server mainly completes the following tasks and can be managed by continuity care nurses (chronic disease management nurses, etc.):

[0129] According to the pressure injury stage and area of ​​the pressure injury patients shared by the cloud server, it is determined whether to conduct additional assessments and to determine the factors affecting wound healing (such as the effects of myosin and blood sugar on wound healing) in combination with the patient's wound condition, daily medication, diet, etc., and to implement corresponding systemic and local treatment care and intervention measures. These nursing measures issued by the continuity care server can also be fed back to the cloud server, which will be synchronized to the corresponding patient's caregiver, allowing them to care for the patient according to the nursing measures.

[0130] The nursing education module can store vivid nursing education, vivid publicity guidance, and health education content. Specifically, it can pre-configure chronic disease education measures corresponding to different stages (which can be pictures, texts, videos, etc.). After receiving the current patient's chronic disease stage feedback from the cloud server, it can automatically match and recommend corresponding chronic disease education measures and publicity guidance according to the stage (that is, the continuity nursing education data recommended for patients can be sent to the cloud server (recorded and saved by the HIS system), and recommended by the cloud server to the patient side and EDA nursing terminal, so that patients and caregivers can view their own trauma development and stage, area and corresponding nursing education data, etc. through the terminal device).

[0131] Patients and caregivers can log in to the cloud server through corresponding terminal devices such as mini-programs, web pages or apps. After identity authentication and authorization, they can log in and view the chronic disease management information recorded on the cloud server.

[0132] In each subsequent evaluation, the staging, area, and nursing education data of the above patients can be recorded for tracking management.

[0133] The wound nursing annotation module is mainly used to perform nursing annotation of wound images: photographing wounds to quickly and accurately assess pressure injury wounds, providing replicable operating methods, building a case management library, seamlessly connecting continuity of care, accelerating wound healing, reducing medical costs, and alleviating socioeconomic burdens.

[0134] As attached Figure 5 As shown, if the patient is in stage 2, corresponding graphic annotations can be made on the wound image, and the nursing measures recommended by the system can be annotated on the wound image to form a wound nursing guidance map, which can be sent to nurses, etc., so that the nurses can view the wound nursing guidance map and perform nursing according to the instructions on the map. This method of annotating drawings and using accurate text and image processing methods on the wound surface allows nursing staff to simply copy and use it for clinical nursing guidance.

[0135] As an optional implementation scheme of the present application, optionally, the chronic disease management module is also used for:

[0136] Sharing the wound care guidance diagram of each recorded pressure injury patient to the cloud server;

[0137] The cloud server is also used for:

[0138] The wound care guidance diagram of each recorded pressure injury patient is recorded in the HIS system and saved under the consultation ID of the pressure injury patient.

[0139] The chronic disease management module can compile statistics for each patient's assessment, recommendation, guidance and other data to generate a chronic disease management file for the patient during the continuity of care stage, which is convenient for diagnosis and treatment tracking.

[0140] like Figure 4 As shown, as an optional implementation scheme of the present application, optionally, the system further includes:

[0141] The EDA nursing terminal is used to request the cloud server to view the pressure injury clinical information of the pressure injury patient; and after the cloud server responds to the request, log in to the cloud server and enter the HIS system to view the first pressure injury clinical information of the corresponding pressure injury patient;

[0142] The patient end is used to log in to the cloud server and enter the HIS system to view the clinical information of the second pressure injury bound to the patient's medical ID;

[0143] a third-party backend server, configured to request the cloud server to share the pressure injury clinical information of the pressure injury patient; and, after the cloud server responds to the request, receive and view the third pressure injury clinical information of the corresponding pressure injury patient returned by the cloud server;

[0144] The first pressure injury clinical information, the second pressure injury clinical information and the third pressure injury clinical information include the following information:

[0145] The wound images of patients with pressure injuries at different stages and their corresponding wound features, the pressure injury staging, the wound area and / or the wound care guidance map.

[0146] In this solution, the cloud server and the continuity care server interact with each other to generate the patient's chronic disease staging status, area, and recommended chronic disease clinical guidance and education data in each stage. This information can be synchronously written into the HIS system, and the patient's chronic disease management data throughout the treatment stage can be saved in the HIS system. Medical staff, patients, etc. log in to the cloud server and view it. In order to achieve global management of chronic diseases and allow chronic disease patients to receive global treatment and care, nursing staff, patients, and third parties can request and share chronic disease management data, so that chronic disease patients can achieve continuity of diagnosis and treatment of chronic diseases in different scenarios (such as transfer).

[0147] Backstage nurses can view the patient's clinical information through EDA. Patients can choose to view their own information. The third-party backstage server needs to send a sharing request to the cloud server, requesting the cloud server to share the patient's pressure injury clinical information. At this time, the cloud server administrator needs to review the sharing request submitted by the third-party backstage server, respond after the review is passed, and then return the corresponding patient's pressure injury clinical information to the third party for viewing.

[0148] The cloud server's identity authentication and authority management for different subjects are specifically set by the cloud server's backend administrator, and this solution does not limit this. The cloud server shares and feedbacks the patient's pressure injury clinical information to different subjects, which can be determined by the backend administrator and can be fed back according to the content requested by each subject.

[0149] Therefore, the present invention can shorten the time for nursing staff to assess pressure injuries; improve the accuracy of wound assessment; provide nursing staff with accurate treatment and nursing methods for pressure injuries; accelerate the healing of pressure injuries; and establish a chronic disease case management database for patients with pressure injuries for resource sharing.

[0150] Obviously, those skilled in the art should understand that the implementation of all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. Those skilled in the art can understand that the implementation of all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (Flash Memory), a hard disk (Hard Disk Drive, abbreviated as: HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0151] Example 2

[0152] like Figure 6 As shown, based on the implementation principle of Example 1, on the other hand, the present application proposes an application method of the intelligent assessment and diagnosis system for pressure injuries in continuity care, which is implemented based on the intelligent assessment and diagnosis system for pressure injuries, and includes the following steps:

[0153] The wound surface images of patients with pressure injuries are collected through the wound surface image acquisition system and sent to the cloud server;

[0154] The cloud server receives and processes the wound surface image, intelligently evaluates the pressure injury stage of the pressure injury patient and calculates the corresponding wound surface area according to the wound surface image, and sends the pressure injury stage and the wound surface area of ​​the pressure injury patient to the continuity care server;

[0155] The continuity care server intelligently determines corresponding continuity care education data for the pressure injury patient based on the pressure injury staging and the wound area.

[0156] Please understand and implement the above specific application method in conjunction with the principles in Example 1.

[0157] The modules or steps of the present invention described above can be implemented by a general-purpose computing system, they can be concentrated on a single computing system, or distributed on a network composed of multiple computing systems, and optionally, they can be implemented by a program code executable by a computing system, so that they can be stored in a storage system and executed by the computing system, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0158] Example 3

[0159] like Figure 7 As shown, further, in another aspect, the present application also proposes an electronic device, including:

[0160] processor;

[0161] a memory for storing processor-executable instructions;

[0162] Wherein, the processor is configured to implement the application method described in Example 2 when executing the executable instructions.

[0163] The electronic device of the embodiment of the present disclosure includes a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to implement the application method described in the above embodiment 2 when executing the executable instructions.

[0164] Here, it should be noted that the number of processors can be one or more. At the same time, the electronic device of the embodiment of the present disclosure may also include an input system and an output system. Among them, the processor, memory, input system and output system may be connected through a bus or in other ways, which are not specifically limited here.

[0165] As a computer-readable storage medium, the memory can be used to store software programs, computer executable programs and various modules, such as: a program or module corresponding to an application method of Embodiment 2 of the present disclosure. The processor executes various functional applications and data processing of the electronic device by running the software programs or modules stored in the memory.

[0166] The input system can be used to receive input numbers or signals. The signal can be a key signal related to user settings and function control of the device / terminal / server. The output system can include display devices such as display screens.

[0167] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. An intelligent pressure injury assessment and diagnosis system, characterized in that: The system comprises: Wound surface image acquisition system, used to collect wound surface images of patients with pressure injuries and send them to the cloud server; A cloud server, configured to receive and process the wound surface image, intelligently evaluate the pressure injury stage of the pressure injury patient and calculate the corresponding wound surface area according to the wound surface image, and send the pressure injury stage and the wound surface area of ​​the pressure injury patient to a continuity care server; A continuity care server, for intelligently making decisions on corresponding continuity care education data for patients with pressure injuries based on the location and stage of the pressure injury and the wound area; The wound surface image acquisition system and the continuity care server are respectively communicatively connected to the cloud server.

2. The intelligent assessment and diagnosis system for pressure injuries according to claim 1, characterized in that: The cloud server comprises: A pressure injury AI assessment model, used to extract image features from the wound surface image and perform wound surface feature recognition, and output the recognized wound surface features; A staging assessment module, for assessing and outputting the current pressure injury stage of the pressure injury patient according to the identified wound surface characteristics; A wound surface contour extraction module, used for marking and extracting the wound surface contour of the wound surface feature on the wound surface image according to the expression characteristics of the wound surface feature on the wound surface image; An area calculation module, used to calculate the area of ​​the wound surface contour to calculate the corresponding wound surface area; The HIS system is used to record the pressure injury stage and the wound area of ​​the pressure injury patient and save them under the patient's consultation ID; and synchronously send each recorded pressure injury stage and wound area to the continuity care server.

3. The intelligent assessment and diagnosis system for pressure injuries according to claim 2, characterized in that: The method for generating the pressure injury AI assessment model comprises: Acquiring a training data set, wherein the training data set includes wound images at different pressure injury stages; Performing feature engineering on wound images at different pressure injury stages in the training data set, extracting image features of wound images at different pressure injury stages, and constructing a corresponding wound image feature data set; Based on a convolutional neural network, the image features of wound images at different pressure injury stages in the wound image feature data set are trained and learned to generate the pressure injury AI assessment model; Randomly collect clinical wound images of patients with pressure injuries as a validation set, and use the validation set to evaluate and validate the pressure injury AI assessment model; If qualified, the pressure injury AI assessment model is deployed on the cloud server to intelligently identify the image features of wound images of pressure injury patients at different pressure injury stages.

4. The intelligent pressure injury assessment and diagnosis system according to claim 2, characterized in that: The continuing care server comprises: A nursing education module, which is used to automatically match the continuity nursing education data corresponding to the pressure injury stage according to the pressure injury site and stage of the pressure injury patient; A wound care annotation module, used to annotate the continuity care education data on the wound image of the pressure injury patient and generate a corresponding wound care guidance diagram; The chronic disease management module is used to manage chronic diseases of patients with pressure injuries, including: recording and saving the pressure injury staging, wound area and wound care guidance chart of patients with pressure injuries at different stages.

5. The intelligent assessment and diagnosis system for pressure injuries according to claim 4, characterized in that: The chronic disease management module is also used for: Sharing the wound care guidance diagram of each recorded pressure injury patient to the cloud server; The cloud server is also used for: The wound care guidance diagram of each recorded pressure injury patient is recorded in the HIS system and stored under the consultation ID of the pressure injury patient.

6. The intelligent pressure injury assessment and diagnosis system according to claim 5, characterized in that: The system further comprises: The EDA nursing terminal is used to request the cloud server to view the pressure injury clinical information of the pressure injury patient; and after the cloud server responds to the request, log in to the cloud server and enter the HIS system to view the first pressure injury clinical information of the corresponding pressure injury patient; The patient end is used to log in to the cloud server and enter the HIS system to view the clinical information of the second pressure injury bound to the patient's medical ID; a third-party backend server, configured to request the cloud server to share the pressure injury clinical information of the pressure injury patient; and, after the cloud server responds to the request, receive and view the third pressure injury clinical information of the corresponding pressure injury patient returned by the cloud server; The first pressure injury clinical information, the second pressure injury clinical information and the third pressure injury clinical information include the following information: The wound images of patients with pressure injuries at different stages and their corresponding wound features, the pressure injury staging, the wound area and / or the wound care guidance map.

7. A method for applying a pressure injury intelligent assessment and diagnosis system in continuity care, which is implemented based on the pressure injury intelligent assessment and diagnosis system according to any one of claims 1 to 6, characterized in that: The steps include: The wound surface images of patients with pressure injuries are collected through the wound surface image acquisition system and sent to the cloud server; The cloud server receives and processes the wound surface image, intelligently evaluates the pressure injury stage of the pressure injury patient and calculates the corresponding wound surface area according to the wound surface image, and sends the pressure injury stage and the wound surface area of ​​the pressure injury patient to the continuity care server; The continuity care server intelligently determines corresponding continuity care education data for the pressure injury patient based on the pressure injury staging and the wound area.

8. An electronic device, characterized in that include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to implement the application method described in claim 7 when executing the executable instructions.

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