Intelligent medical guide system

Abstract

The invention relates to the field of medical informatization, in particular to an intelligent medical guidance system. The intelligent medical guide system integrates multiple modules of information acquisition, data processing, position positioning, path planning, information pushing, human-computer interaction and the like into a whole, and the whole-process intelligentization of patient identification, positioning, navigation and information service is realized. The system collects a facial image and card type information of a patient and generates an identity recognition result; planning a navigation path according to the position coordinates and the hospital structure; and personalized treatment reminding is pushed. The human-computer interaction interface displays paths and prompts and receives a patient instruction. The system improves hospital operation efficiency and medical quality, innovates man-machine interaction and data security, improves medical experience, provides powerful support for hospital management and medical service quality improvement, and realizes organic combination of accurate and personalized medical service and efficient hospital management.

Description

Technical Field

[0001] The present invention relates to the field of medical informatization, and particularly to an intelligent medical guidance system. Background Art

[0002] With the rapid development of the medical and health cause, the scale of large general hospitals has been continuously expanding, and their functions have become increasingly complex. Patients often face problems such as getting lost, long waiting times, and untimely access to information during the medical treatment process, which not only affects the patients' medical experience but also reduces the operating efficiency of the hospital. To solve these problems, major hospitals have begun to introduce medical guidance systems one after another.

[0003] Traditional medical guidance systems mainly rely on manual services. Although they can provide basic guidance for patients, they are often overwhelmed when faced with a large number of patients. With the progress of technology, some hospitals have started to use devices such as electronic navigation signs and self-service inquiry machines to assist in medical guidance work. These devices have improved the medical guidance efficiency to a certain extent, but there are still many limitations. For example, electronic navigation signs usually can only provide static path information and cannot be adjusted according to real-time situations; although self-service inquiry machines can provide more information, they are complex to operate and not user-friendly for special groups such as the elderly.

[0004] In recent years, with the development of artificial intelligence technology, some hospitals have begun to try to introduce intelligent medical guidance systems. Such systems usually combine technologies such as face recognition and indoor positioning and can provide personalized navigation services for patients. However, the existing intelligent medical guidance systems still have some obvious deficiencies. First of all, most systems only focus on the navigation function and ignore other needs of patients during the medical treatment process, such as appointment reminders and examination preparations. Secondly, the human-computer interaction methods of the systems are often single and difficult to meet the usage habits of different patients. Moreover, the existing systems generally lack the ability to adapt to the dynamic environment of the hospital and cannot effectively handle emergencies such as temporarily closed areas and crowded people. In addition, in terms of data security and privacy protection, many systems also have deficiencies and are difficult to meet the increasingly strict medical data protection requirements.

[0005] In view of the above problems, there is an urgent need for a comprehensive, intelligent, and secure medical guidance system that can provide full-process services for patients from admission to discharge, and at the same time has good adaptability and scalability to adapt to the changing medical environment and patient needs. Summary of the Invention

[0006] The purpose of the present invention is to provide an intelligent medical guidance system, aiming to solve the problems of the existing medical guidance systems such as single function, rigid interaction method, poor environmental adaptability, and insufficient data security. The intelligent medical guidance system of the present invention realizes functions such as intelligent collection of patient information, precise positioning, dynamic navigation, personalized information push, and medical staff collaboration through the coordinated work of multiple modules, while paying attention to data security and system optimization.

[0007] The present invention provides an intelligent medical guidance system, including:

[0008] An information acquisition module, configured to:

[0009] Acquire the facial image information of the patient;

[0010] Obtain the card recognition information of the patient;

[0011] A data processing module, communicatively connected to the information acquisition module, configured to:

[0012] Receive the patient information sent by the information acquisition module;

[0013] Generate a patient identity recognition result based on the patient information;

[0014] A location positioning module, configured to:

[0015] Obtain the current location coordinates of the patient;

[0016] Obtain the hospital building structure information;

[0017] A path planning module, communicatively connected to the data processing module and the location positioning module, configured to:

[0018] Receive the patient identity recognition result sent by the data processing module;

[0019] Receive the current location coordinates of the patient and the hospital building structure information sent by the location positioning module;

[0020] Generate a navigation path based on the patient identity recognition result, the current location coordinates of the patient, and the hospital building structure information;

[0021] An information push module, communicatively connected to the data processing module, configured to:

[0022] Receive the patient identity recognition result sent by the data processing module;

[0023] Obtain the patient's medical treatment information from the hospital information system based on the patient identity recognition result;

[0024] Push personalized medical treatment reminders to the patient;

[0025] A human-computer interaction module, configured to:

[0026] Display the navigation path generated by the path planning module;

[0027] Display the medical treatment reminders pushed by the information push module;

[0028] Receive the interaction instructions of the patient.

[0029] Preferably, the information collection module includes:

[0030] A face recognition unit for collecting facial image information of the patient;

[0031] A card type recognition unit for reading the information of the patient's medical insurance card or visiting card;

[0032] A voice collection unit for collecting the voice information of the patient;

[0033] Among them, the face recognition unit, the card type recognition unit and the voice collection unit are all communicatively connected to the data processing module.

[0034] Preferably, the data processing module includes:

[0035] An identity recognition unit for generating a patient identity recognition result based on the patient information through data comparison with the hospital information system;

[0036] A data fusion unit for performing multi-modal fusion on the facial image information, card type recognition information and voice information to improve the accuracy of identity recognition.

[0037] Preferably, the location positioning module includes:

[0038] A Beidou positioning unit for obtaining the approximate location of the patient in the hospital;

[0039] An indoor positioning unit for accurately positioning the specific location of the patient in the hospital through the Wi-Fi or Bluetooth beacon network in the hospital;

[0040] A building information unit for storing and managing the building information model (BIM) data of the hospital.

[0041] Preferably, the path planning module includes:

[0042] A path calculation unit for calculating the optimal navigation path based on the current location and target location of the patient in combination with the hospital building structure information;

[0043] A dynamic adjustment unit for dynamically adjusting the navigation path according to the real-time congestion situation or temporarily closed area.

[0044] Preferably, the information push module includes:

[0045] A medical treatment information acquisition unit for obtaining the patient's medical treatment arrangements, examination items and precautions from the hospital information system;

[0046] A personalized push unit for pushing corresponding reminder information according to the patient's medical treatment progress and location;

[0047] The escort management unit is used to determine whether an escort is needed according to the patient's condition and provide an escort reservation service.

[0048] Preferably, the human-computer interaction module includes:

[0049] A display unit for graphically displaying the navigation path and appointment reminders;

[0050] A touch control unit for receiving touch operation instructions from the patient;

[0051] A voice interaction unit for performing speech recognition and speech synthesis to achieve voice conversations with the patient;

[0052] A gesture recognition unit for recognizing the patient's facial expressions and head movements to judge the patient's status and needs.

[0053] Preferably, it further includes:

[0054] A medical staff collaboration module, communicatively connected to the data processing module, for:

[0055] Receiving the patient identification result sent by the data processing module;

[0056] Based on the patient identification result, sharing patient information among medical staff;

[0057] Coordinating the work arrangements of medical staff.

[0058] Preferably, it further includes:

[0059] A data security module, communicatively connected to the data processing module, for:

[0060] Encrypting and storing patient information;

[0061] Managing system access permissions;

[0062] Recording data operation logs.

[0063] Preferably, it further includes:

[0064] A system optimization module, communicatively connected to the data processing module, for:

[0065] Collecting system operation data and user feedback;

[0066] Analyzing the system usage effect;

[0067] Generating system optimization suggestions.

[0068] The intelligent medical guidance system of the present invention has the following remarkable beneficial effects:

[0069] First, the present invention realizes the rapid and accurate identification of the patient's identity through the collaborative work of the information collection module and the data processing module. The system adopts multimodal information fusion technology, combined with facial recognition, card recognition and voice recognition, etc., which greatly improves the accuracy and convenience of identity recognition. This not only simplifies the patient's medical treatment process, but also lays the foundation for subsequent personalized services.

[0070] Secondly, the location positioning module and path planning module of the present invention cooperate with each other to provide patients with accurate and real-time navigation services. The system innovatively combines Beidou, Wi-Fi and Bluetooth beacon technologies to achieve seamless indoor and outdoor positioning. At the same time, the improved multi-objective A* algorithm is used for path planning, which not only takes into account the distance factor, but also introduces multi-dimensional indicators such as congestion level and patient preferences, and can provide patients with the best navigation solution. This dynamic and intelligent navigation service greatly reduces the possibility of patients getting lost or taking detours in the hospital, and improves the efficiency of medical treatment.

[0071] Furthermore, the information push module and the human-computer interaction module of the present invention jointly construct an intelligent and user-friendly interface. Based on the reinforcement learning algorithm, the system realizes personalized information push and can provide patients with key information such as medical reminders and examination preparation guidance at the right time. The multimodal human-computer interaction design, including touch, voice and gesture recognition, enables the system to adapt to the usage habits of different patients, especially providing a more convenient user experience for special groups such as the elderly and the disabled.

[0072] In addition, the present invention also has important innovations in medical collaboration and data security. The medical collaboration module realizes the secure sharing of patient information and the optimal scheduling of medical resources by introducing blockchain technology. The data security module adopts advanced technologies such as homomorphic encryption, which protects patient privacy without affecting the analysis and use of data. These innovations not only improve the quality and efficiency of medical services, but also provide a higher level of protection for patient data.

[0073] Finally, the system optimization module of the present invention gives the system the ability to continuously evolve. Through real-time data collection and deep learning analysis, the system can continuously optimize its own performance to adapt to the dynamic changes in the hospital environment and the diversity of patient needs. This adaptive optimization mechanism greatly extends the life cycle of the system and ensures its long-term effectiveness and advancement.

[0074] In summary, through the organic combination and collaborative work of multiple functional modules, the intelligent medical guidance system of the present invention realizes the full-process intelligent management from patient identification, location positioning, path planning to information push and medical staff collaboration. The system can not only provide accurate and personalized navigation and information services for patients, but also effectively improve the operation efficiency and medical quality of the hospital. In particular, the innovations in human-computer interaction, data security and system optimization enable the system to not only improve the patient's medical experience, but also provide strong support for the improvement of hospital management and medical service quality. This all-round and intelligent medical guidance system will greatly promote the development of medical services towards a more user-friendly and efficient direction, and provide important technical support for building a smart hospital. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 is the overall architecture diagram of the system of the present invention;

[0076] Figure 2 is the information collection module diagram of the present invention;

[0077] Figure 3 is the data processing module diagram of the present invention;

[0078] Figure 4 is the location positioning module diagram of the present invention;

[0079] Figure 5 is the path planning module diagram of the present invention;

[0080] Figure 6 is the information push module diagram of the present invention;

[0081] Figure 7 is the human-computer interaction module diagram of the present invention;

[0082] Figure 8 is the medical staff collaboration module diagram of the present invention;

[0083] Figure 9 is the data security module diagram of the present invention;

[0084] Figure 10 is the system optimization module diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0085] Please refer to the attached Figures 1 - 10 , the present invention provides an intelligent medical guidance system, which can effectively improve the medical treatment efficiency of the hospital and the medical experience of patients. The present invention will be described in detail below in conjunction with the specific embodiments.

[0086] The intelligent medical guidance system of the present invention includes an information collection module 1, a data processing module 2, a position positioning module 3, a path planning module 4, an information push module 5, and a human-computer interaction module 6. These modules are interconnected through a data bus and cooperate with each other to achieve the intelligent medical guidance function.

[0087] The information collection module 1 is used to collect the facial image information of the patient and obtain the card type recognition information of the patient. Preferably, the information collection module 1 includes a high-definition camera set at the hospital entrance, self-service terminal or clinic door for capturing the facial image of the patient. In addition, the information collection module 1 also includes a card reading device that can read the patient's medical insurance card, visit card or other identity recognition cards. This multi-modal information collection method can improve the accuracy and convenience of identity recognition.

[0088] The data processing module 2 is communicatively connected to the information collection module 1, and is used to receive the patient information sent by the information collection module 1 and generate a patient identity recognition result based on this information. In an embodiment of the present invention, the data processing module 2 uses a deep learning algorithm for facial feature extraction and matching. Specifically, a convolutional neural network (CNN) can be used to extract facial features, and then identity matching is performed through cosine similarity calculation. Let the facial feature vector be The known identity feature vector in the database is Then the similarity S can be calculated by the following formula:

[0089]

[0090] Where, represents the dot product of the two vectors, and respectively represent the Euclidean norms of the two vectors. When the similarity s exceeds a preset threshold (for example, 0.85), the identity matching is considered successful. The selection of this threshold is based on a large amount of experimental data, taking into account the influence of factors such as light and angle in actual applications while ensuring the recognition accuracy.

[0091] The position positioning module 3 is used to obtain the current position coordinates of the patient and the hospital building structure information. In the preferred implementation manner of the present invention, the position positioning module 3 adopts a hybrid positioning technology, combining Beidou, Wi-Fi and Bluetooth beacons for seamless indoor and outdoor positioning. For outdoor areas, it mainly relies on Beidou signals; while in indoor environments, the system will automatically switch to the Wi-Fi and Bluetooth beacon networks for precise positioning. The position positioning module 3 also includes a building information database that stores the detailed floor plan of the hospital and the distribution information of each functional area.

[0092] The path planning module 4 is communicatively connected to the data processing module 2 and the position positioning module 3, and is used to receive the patient identity recognition result, the current position coordinates, and the hospital building structure information, and generate a navigation path based on this information. In practical applications, the path planning module 4 uses an improved A* algorithm for path search. The core idea of this algorithm is to select the optimal path through the evaluation function f(n):

[0093] f(n) = g(n) + h(n),

[0094] where n is the current node, g(n) is the actual cost from the starting point to node N, and h(n) is the estimated cost from node n to the target point. The present invention improves the traditional A* algorithm by introducing a dynamic weight factor w to balance efficiency and comfort:[[]]END]]

[0095] f(n) = g(n) + w·h(n),

[0096] The value range of the weight factor w is [0.5, 1.5], and it is dynamically adjusted according to the current hospital congestion level. When the hospital has a large number of people, the value of w is small, and it tends to choose a shorter but possibly crowded path; when the number of people is small, the value of w is large, and it will choose a relatively comfortable path, even if the distance is slightly longer. This dynamic adjustment mechanism can provide the most suitable navigation plan for patients in different situations.[[]]END]]

[0097] The information push module 5 is communicatively connected to the data processing module 2, and is used to receive the patient identity recognition result, obtain the patient's medical treatment information from the hospital information system based on this result, and push personalized medical treatment reminders to the patient. An innovation of the present invention is that the information push module 5 adopts an intelligent push algorithm, and automatically adjusts the push frequency and content according to the patient's medical treatment progress, waiting time, and current position. For example, when the patient is about to be seen, the system will send more frequent reminders; if the examination item requires special preparation, the system will push the relevant precautions in advance.[[]]END]]

[0098] The human-computer interaction module 6 is used to display the navigation path generated by the path planning module 4, the medical treatment reminder pushed by the information push module 5, and receive the interaction instructions of the patient. In an embodiment of the present invention, the human-computer interaction module 6 adopts multimodal interaction technology, including touch screen operation, voice dialogue, and gesture recognition. In particular, the system integrates natural language processing technology and can understand the patient's colloquial instructions, such as "I want to see a dentist", and the system will automatically convert it into a corresponding department navigation request.[[]]END]]

[0099] Through the collaborative work of the above modules, the intelligent medical guidance system of the present invention realizes the intelligent guidance for the whole process from the patient's admission to discharge. The system can not only provide accurate indoor navigation, but also offer personalized medical advice and reminders according to the specific situation of the patient. This intelligent medical guidance service greatly improves the operation efficiency of the hospital and significantly enhances the patient's medical experience.

[0100] In another embodiment of the present invention, the information collection module 1 further includes a voice collection unit 11 for collecting the voice information of the patient. The voice collection unit 11 can be an independent microphone array or integrated in the self-service terminal. By introducing voice information, the system can achieve a more natural human-computer interaction, which is especially suitable for the elderly or patients who are inconvenient to operate the touch screen.

[0101] In this embodiment, the data processing module 2 further includes an identity recognition unit 21 and a data fusion unit 22. The identity recognition unit 21 is responsible for generating the patient identity recognition result based on the collected patient information by comparing with the data in the hospital information system. The data fusion unit 22 performs multi-modal fusion on the facial image information, card type recognition information and voice information to improve the accuracy of identity recognition.

[0102] In the multi-modal fusion process, the present invention adopts a weighted fusion strategy. Let the confidence levels of face recognition, card type recognition and voice recognition be C f 、C c and C v , then the final identity recognition confidence level C can be expressed as:

[0103] C = w f C f + w c C c + w v C v ,

[0104] where w f , w c and w v are the weights of each modality respectively, and satisfy w f + w c + w v = 1. These weights can be dynamically adjusted according to the actual application scenario. For example, in an environment with relatively dim light, the weight of face recognition can be appropriately reduced and the weight of voice recognition can be increased.

[0105] Through this multi-modal fusion approach, the intelligent medical guidance system of the present invention can maintain highly accurate identity recognition in various complex environments, providing a reliable basis for subsequent personalized services. At the same time, this flexible fusion strategy also enables the system to have good scalability, and in the future, other biometric recognition technologies, such as iris recognition or gait recognition, can be conveniently integrated.

[0106] Through the close cooperation of the above-mentioned modules and units, the intelligent medical guidance system of the present invention realizes the intelligent acquisition, processing, and application of patient information. The system can not only quickly and accurately identify the patient's identity, but also provide personalized navigation and information services based on the recognition results, greatly improving the service quality and operation efficiency of the hospital. Especially in large general hospitals, this system can effectively reduce the patient's lost and waiting time and improve the medical treatment satisfaction.

[0107] In a preferred embodiment of the present invention, the position positioning module 3 includes a Beidou positioning unit 31, an indoor positioning unit 32, and a building information unit 33. This diversified positioning solution can achieve seamless positioning inside and outside the hospital, providing a full-range navigation service for patients.

[0108] The Beidou positioning unit 31 is mainly used to obtain the approximate position of the patient in the external area of the hospital. When the patient enters the hospital, the system will automatically switch to a more accurate indoor positioning mode. The indoor positioning unit 32 adopts an advanced method combining Wi-Fi fingerprint positioning technology and Bluetooth beacon network to achieve high-precision indoor positioning. Preferably, the Wi-Fi fingerprint positioning adopts a positioning algorithm based on deep learning, and the neural network model is trained through the pre-collected Wi-Fi signal strength data to achieve sub-meter positioning accuracy. Specifically, let S=(s1, s2,..., s n ) be the signal strength vector of n Wi-Fi access points received at a certain position, then the position estimation can be expressed as:

[0109]

[0110] where f(·) represents the trained deep neural network model, is the estimated position coordinate. The neural network model adopted by the present invention includes multiple convolutional and fully connected layers, which can effectively capture the spatial correlation of Wi-Fi signal strength and improve the positioning accuracy.

[0111] The building information unit 33 stores and manages the building information model (BIM) data of the hospital. These data not only include the floor plan of the hospital, but also contain the vertical connection relationships of each floor, the attribute information of each functional area, etc. By combining with accurate location information, the system can provide more intelligent and user-friendly navigation services for patients. For example, the system can automatically select whether to give priority to using elevators or accessible passages according to the patient's mobility ability.

[0112] In an embodiment of the present invention, the path planning module 4 further includes a path calculation unit 41 and a dynamic adjustment unit 42. The path calculation unit 41 is responsible for calculating the optimal navigation path based on the patient's current location and the target location, in combination with the hospital building structure information. In the process of path calculation, the present invention adopts an improved multi-objective A* algorithm, taking into account multiple factors such as path length, congestion level, and patient preferences. Let x = (x1, x2,..., x m ) be m nodes on the path, then the path evaluation function can be expressed as:

[0113] F(x) = w1L(x) + w2C(x) + w3P(x),

[0114] where L(x), C(x), and P(x) respectively represent the evaluation functions of path length, congestion level, and patient preferences, and w1, w2, and w3 are the corresponding weight coefficients. These weights can be dynamically adjusted according to the actual situation. For example, during the epidemic period, the weight of the congestion level can be increased to avoid crowd gathering as much as possible.

[0115] The dynamic adjustment unit 42 is used to dynamically adjust the navigation path according to the real-time congestion situation or temporarily closed areas. The system of the present invention monitors the congestion situation in real time through the people flow sensors distributed throughout the hospital, and continuously updates the path planning strategy using an online learning algorithm. This dynamic adjustment mechanism can effectively respond to the changes in the hospital internal environment and provide the latest and optimal navigation solutions for patients.

[0116] In another embodiment of the present invention, the information push module 5 includes a medical appointment information acquisition unit 51, a personalized push unit 52, and a companion management unit 53. The medical appointment information acquisition unit 51 obtains information such as the patient's medical appointment arrangements, examination items, and precautions by real-time docking with the hospital information system. The personalized push unit 52 then intelligently pushes the corresponding reminder information according to the patient's medical appointment progress and location.

[0117] One innovation of the present invention lies in the adoption of an intelligent push strategy based on reinforcement learning. The system models the push process as a Markov decision process, where the state space includes factors such as the patient's location, treatment progress, waiting time, etc., and the action space is different types of push messages. Through long-term interaction with patients, the system learns the optimal push strategy to maximize patient satisfaction and medical treatment efficiency. Specifically, let Q(s,a) be the value function of taking action a in state s, then the update rule of the Q function is:

[0118] Q(s,a)←Q(s,a)+α[r+γmax a′ Q(s′,a′)-Q(s,a)],

[0119] where α is the learning rate, γ is the discount factor, r is the immediate reward, and s′ is the next state. By continuously iteratively updating the Q function, the system can learn the optimal push strategy and push the most valuable information to patients at the appropriate time.

[0120] The escort management unit 53 is another innovation of the present invention. It can intelligently judge whether an escort is needed according to the patient's situation and provide an escort reservation service. The system analyzes information such as the patient's age, medical history, current examination items, etc., and uses machine learning algorithms to predict whether the patient needs an escort. If an escort is needed, the system will automatically recommend suitable escort personnel and assist with the reservation. This function greatly improves the utilization efficiency of hospital resources and provides more considerate services for patients with special needs.

[0121] In the embodiment of the present invention, the human-computer interaction module 6 includes a display unit 61, a touch control unit 62, a voice interaction unit 63, and a gesture recognition unit 64. This multi-modal interaction method can adapt to the usage habits and capabilities of different patients and provide a more friendly and barrier-free user experience.

[0122] The display unit 61 adopts a high-definition touch screen to graphically display the navigation path and appointment reminder. The system automatically adjusts the font size and color scheme of the interface according to the patient's age and vision conditions to ensure clear readability of the information. The touch control unit 62 supports multi-touch and gesture operations, facilitating quick and intuitive operations by patients.

[0123] The voice interaction unit 63 integrates advanced speech recognition and natural language processing technologies and can understand the patient's colloquial instructions. For example, when the patient says "I want to see a dentist", the system will automatically recognize the intention and convert it into a navigation request to the dentistry department. In addition, the voice interaction unit 63 also supports multiple dialects and languages, greatly improving the universality of the system.

[0124] The gesture recognition unit 64 is another innovation of the present invention. It can capture the patient's facial expressions and body movements through a camera to judge the patient's emotional state and potential needs. For example, if the system detects that the patient shows an anxious or confused expression, it will actively ask if help is needed. This interaction method based on emotional computing makes the system more user-friendly and can provide more considerate services for patients.

[0125] Through the collaborative work of the above modules and units, the intelligent medical guidance system of the present invention realizes all-round, high-precision, and personalized patient services. The system can not only accurately guide patients to navigate in a complex hospital environment, but also provide customized information push and interaction services according to the specific situation of patients. This intelligent medical guidance method greatly improves the service quality and operation efficiency of the hospital, and at the same time significantly improves the patient's medical experience. Especially for special groups such as the elderly and the disabled, the value of this system is more prominent.

[0126] In another preferred embodiment of the present invention, the intelligent medical guidance system further includes a medical staff collaboration module 7, which is communicatively connected to the data processing module 2 and is used to receive the patient identity recognition result sent by the data processing module 2, share patient information among medical staff based on this result, and coordinate the work arrangements of medical staff.

[0127] The introduction of the medical staff collaboration module 7 greatly improves the collaboration efficiency within the hospital. This module includes an information sharing unit 71 and a task scheduling unit 72. The information sharing unit 71 is responsible for securely transmitting patient information among different departments and medical staff to ensure that patients receive consistent treatment throughout the medical treatment process. To protect patient privacy, the present invention adopts blockchain-based distributed storage technology to encrypt and store patient information in a decentralized manner. Each information access will be recorded on the blockchain, ensuring the immutability and traceability of the data.

[0128] The task scheduling unit 72 is responsible for dynamically optimizing the allocation of medical resources according to the medical treatment needs of patients and the working status of medical staff. The present invention innovatively introduces a scheduling strategy that combines heuristic algorithms and machine learning here. Specifically, the system first uses an improved genetic algorithm to generate an initial scheduling plan, and then continuously optimizes the scheduling strategy through reinforcement learning. Let X=(x ij ) n×m be the scheduling matrix, where x ij represents whether the i-th patient is assigned to the j-th medical staff, then the scheduling problem can be formalized as:

[0129] min X F(X)=w1T(X)+w2B(X)+w3S(X),

[0130] Among them, T(X), B(X), and S(X) respectively represent the evaluation functions of the total waiting time, load balance degree, and patient satisfaction, and W1, w2, and w3 are the corresponding weight coefficients. Through continuous learning and adjustment, the system can maximize the utilization efficiency of medical resources while ensuring medical quality.

[0131] Preferably, the medical staff collaboration module 7 further includes a remote consultation unit 73, which supports remote collaboration between different departments or different hospitals. This unit integrates high-definition video communication and medical image sharing functions, enabling complex cases to be promptly consulted by multiple experts, greatly improving the diagnosis and treatment efficiency of difficult and miscellaneous diseases.

[0132] The intelligent medical guidance system of the present invention further includes a data security module 8, which is communicatively connected to the data processing module 2 and is used for encrypting and storing patient information, managing system access permissions, and recording data operation logs. In today's increasingly complex network environment, the security and privacy protection of medical data are particularly important.

[0133] The data security module 8 includes an encrypted storage unit 81, a permission management unit 82, and a log recording unit 83. The encrypted storage unit 81 uses the Advanced Encryption Standard (AES) algorithm to encrypt sensitive patient information. To further improve security, the present invention innovatively introduces homomorphic encryption technology, allowing direct data analysis and processing in the encrypted state, avoiding potential security risks during the intermediate decryption process.

[0134] Let m be the original data and k be the key, then the encryption process can be expressed as:

[0135] c = E(m, k),

[0136] where E(·) represents the encryption function and c is the ciphertext. The characteristics of homomorphic encryption ensure that the operation results of ciphertexts c1 and c2 are equivalent to the results after encrypting the corresponding plaintexts after operation, that is:

[0137]

[0138] This characteristic enables the system to perform necessary data analysis and statistics while protecting patient privacy.

[0139] The permission management unit 82 adopts a role-based access control (RBAC) model to finely manage the access permissions of different users to system functions and data. The system defines multiple roles, such as doctors, nurses, administrators, etc., and each role has a specific set of permissions. In addition, the present invention also introduces a dynamic permission adjustment mechanism to automatically adjust access permissions according to the urgency of the medical scenario. For example, in the case of an emergency, the data access level of certain medical staff is temporarily elevated.

[0140] The log recording unit 83 is responsible for recording all data operation behaviors in the system. In order to ensure the integrity and immutability of the log, the present invention uses blockchain technology to store key operation logs. Each operation is packaged into a transaction, and multiple transactions form a block. The consistency and traceability of the log are ensured through the consensus mechanism. This method not only improves the security of the system, but also provides a reliable basis for subsequent audits and accountability.

[0141] In another embodiment of the present invention, the intelligent medical guidance system also includes a system optimization module 9, which is in communication with the data processing module 2 and is used to collect system operation data and user feedback, analyze system usage effects, and generate system optimization suggestions.

[0142] The system optimization module 9 includes a data collection unit 91, an effect analysis unit 92 and an optimization suggestion unit 93. The data collection unit 91 comprehensively collects system operation data, including user operation tracks, response time, resource utilization, etc., through sensors and log systems distributed in various modules of the system. At the same time, the unit also collects user feedback through questionnaires and sentiment analysis.

[0143] The effect analysis unit 92 uses advanced data mining and machine learning techniques to conduct in-depth analysis of the collected data. The present invention innovatively introduces a multi-dimensional evaluation model here to comprehensively evaluate the operating effect of the system from multiple perspectives such as system performance, user experience, and medical effects. Specifically, the system uses the principal component analysis (PCA) method to reduce the data dimension, and then builds a classification model through the support vector machine (SVM) algorithm to identify potential problems and improvement space in the system. Let X be the original high-dimensional data matrix, then the PCA dimensionality reduction process can be expressed as:

[0144] Y=XW,

[0145] Among them, W is the principal component weight matrix, and Y is the data after dimensionality reduction. The data after dimensionality reduction is input into the SVM model for classification and anomaly detection.

[0146] The optimization suggestion unit 93 generates specific system optimization suggestions based on the results of the effect analysis. The present invention uses a reasoning engine based on a knowledge graph to match the analysis results with a predefined optimization strategy library to generate targeted optimization solutions. For example, if the system detects that certain navigation paths are often congested, the optimization suggestion unit 93 may suggest adjusting the weight parameters of the path planning algorithm, or suggest that the hospital management department add guide signs in relevant areas.

[0147] Through the continuous operation of the system optimization module 9, the intelligent medical guidance system of the present invention can continuously improve and evolve itself to adapt to the dynamic changes of the hospital environment and the diversity of user needs. This adaptive optimization mechanism greatly extends the life cycle of the system and ensures its long-term effectiveness and advancement.

[0148] In summary, the intelligent medical guide system of the present invention realizes intelligent management of the entire process from patient identification, location positioning, route planning to information push, and medical collaboration through the collaborative work of multiple functional modules. The system can not only provide patients with accurate and personalized navigation and information services, but also effectively improve the hospital's operating efficiency and medical quality. In particular, innovations in data security and system optimization enable the system to continuously improve and adapt to the ever-changing medical environment while protecting patient privacy. This all-round, intelligent medical guide system will greatly improve patients' medical experience and promote the development of medical services in a more humane and efficient direction.

[0149] It should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. Intelligent medical guidance system, characterized by ,include: Information collection module, used for: Collect facial image information of patients; Obtain the patient's card identification information; A data processing module is connected to the information acquisition module for: Receiving the patient information sent by the information acquisition module; Based on the patient information, generating a patient identification result; Positioning module for: Get the patient's current location coordinates; Obtain hospital building structure information; A path planning module is communicatively connected with the data processing module and the position positioning module, and is used to: receiving the patient identification result sent by the data processing module; Receiving the patient's current location coordinates and hospital building structure information sent by the location positioning module; Generate a navigation path based on the patient identification result, the patient's current location coordinates and hospital building structure information; The information push module is connected to the data processing module for: receiving the patient identification result sent by the data processing module; Based on the patient identification result, obtaining the patient's medical information from the hospital information system; Send personalized medical appointment reminders to patients; Human-computer interaction module, used for: Display the navigation path generated by the path planning module; Display the medical consultation reminder pushed by the information push module; Receive interactive instructions from patients.

2. The intelligent medical guidance system according to claim 1 is characterized in that , the information collection module includes: A facial recognition unit, used to collect facial image information of the patient; Card identification unit, used to read the patient's medical insurance card or medical card information; A voice collection unit, used to collect the patient's voice information; Wherein, the facial recognition unit, the card type recognition unit and the voice collection unit are all communicatively connected with the data processing module.

3. The intelligent medical guidance system according to claim 1 is characterized in that , the data processing module includes: An identification unit, used to generate a patient identification result based on the patient information by comparing it with the data of the hospital information system; The data fusion unit is used to perform multimodal fusion of the facial image information, card identification information and voice information to improve the accuracy of identity recognition.

4. The intelligent medical guidance system according to claim 1 is characterized in that , the position positioning module includes: Beidou positioning unit, used to obtain the approximate location of the patient in the hospital; Indoor positioning unit, used to pinpoint the patient's specific location within the hospital through the hospital's Wi-Fi or Bluetooth beacon network; Building Information Unit, used to store and manage the hospital's Building Information Model (BIM) data.

5. The intelligent medical guidance system according to claim 1 is characterized in that , the path planning module includes: A path calculation unit, used to calculate the optimal navigation path based on the patient's current location and target location combined with hospital building structure information; The dynamic adjustment unit is used to dynamically adjust the navigation path according to the real-time congestion situation or temporarily closed areas.

6. The intelligent medical guidance system according to claim 1 is characterized in that , the information push module includes: A medical information acquisition unit, used to obtain the patient's medical arrangement, examination items and precautions from the hospital information system; Personalized push unit, used to push corresponding reminder information according to the patient's visit progress and location; The accompanying management unit is used to determine whether accompanying is needed based on the patient's condition and provide accompanying appointment services.

7. The intelligent medical guidance system according to claim 1 is characterized in that , the human-computer interaction module includes: A display unit, used to graphically display the navigation path and the medical consultation reminder; A touch control unit, used for receiving touch operation instructions from the patient; Voice interaction unit, used for voice recognition and speech synthesis to achieve voice dialogue with patients; The gesture recognition unit is used to identify the patient's facial expressions and head movements, and determine the patient's status and needs.

8. The intelligent medical guidance system according to claim 1 is characterized in that , also includes: The medical and nursing collaboration module is connected to the data processing module for: receiving the patient identification result sent by the data processing module; Based on the patient identification result, sharing patient information among medical staff; Coordinate the work arrangements of medical staff.

9. The intelligent medical guidance system according to claim 1 is characterized in that , also includes: A data security module is connected to the data processing module for: Encrypted storage of patient information; Manage system access rights; Record data operation logs.

10. The intelligent medical guidance system according to claim 1 is characterized in that , also includes: A system optimization module, which is in communication with the data processing module, is used to: Collect system operation data and user feedback; Analyze the effectiveness of system usage; Generate system optimization suggestions.

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