33 results about "Hospital based" patented technology

The invention provides a decision tree generation method based on a large language model and related equipment, and is applied to the technical field of data processing. The method comprises the steps of obtaining a training sample set, target medical document information and target hospital information; processing the target hospital information to generate attribute information of the target hospital; the training sample set is preprocessed, a training sample set with target feature data is generated, and the target feature data is used for representing node information and decision path information of clinical guide document information processing; a preset large language model matched with the target feature data is obtained, and the preset large language model is set based on the target hospital information received within the preset time period; training a preset large language model based on the training data set with the target feature data to generate a target large language model; and processing the target medical document information and the attribute information of the target hospital based on the target large language model to generate decision tree information.

The invention relates to the technical field of medical consultation, in particular to an expert registration adaptation system of an internet hospital based on artificial intelligence driving, and the system comprises an artificial intelligence guiding module which automatically obtains the medical record of a patient, and deduces the disease of the patient and a corresponding department; the dynamic number source matching module is based on the real-time number source state, the disease of the patient and the corresponding department, when the system is used, the problem that the patient is difficult to accurately judge which department outpatient service should be applied to the disease due to lack of medical knowledge is effectively solved, accurate department recommendation is provided for the patient through multi-source data fusion analysis, and the patient experience is improved. The accuracy of first registration of a patient is greatly improved, time waste and medical resource mismatching caused by wrong department registration are reduced, meanwhile, through dynamic number source monitoring and an intelligent candidate mechanism and an automatic recommendation replacement expert function, the problem that repeated operation is needed when the patient encounters insufficient number sources when inquiring expert outpatient service information is solved, and the patient experience is improved. The registration time of the patient is greatly saved, and the registration efficiency is improved.

To provide a system that proposes appropriate hospitals based on users' symptoms and unifies formats of medical charts.SOLUTION: A system according to an embodiment includes a reception unit, an identification unit, a proposal unit, a unification unit, and an input unit. The reception unit inputs a user's symptoms. The identification unit identifies an illness based on the information input by the reception unit. The proposal unit proposes a hospital based on the illness identified by the identification unit. The unification unit unifies formats of medical charts. The input unit inputs a diagnosis result.SELECTED DRAWING: Figure 1

The invention discloses an early warning method and system for outbreak of drug-resistant bacteria in a hospital based on dynamic aggregation degree evaluation. The method comprises the following steps: acquiring hospitalization information of a patient, microbiological inspection data and spatial layout information of an inpatient area to obtain initial data; judging whether a new case of drug-resistant bacteria is detected on the current day; if not, gradually reducing the historical aggregation degree by using an exponential decay formula until the historical aggregation degree returns to zero; if yes, calculating a newly added detection rate, a space aggregation degree and a time aggregation degree, and calculating a total aggregation degree of the day; dividing an inpatient area; dynamically generating a threshold value for the high-frequency inpatient area by adopting a quartile method to carry out abnormal value judgment, and identifying an abnormal aggregation degree for the low-frequency inpatient area by using a fixed absolute value threshold mechanism to obtain an early warning level; and early warning information of different levels is pushed according to the early warning level, and a prevention and control suggestion plan is attached. By implementing the method provided by the invention, the accuracy and efficiency of early warning can be remarkably improved, so that patients and medical personnel are better protected from the threat of drug-resistant bacterium infection.

The application discloses a hospital multi-active data center network management system based on a software defined network, relates to the technical field of data management, and discloses a network management system controlled based on an SDN controller, which comprises a traffic collection module, a prediction module, a scheduling module, a multi-active data module and a security module; the traffic collection module is used for collecting historical traffic data of a hospital, analyzing and managing the acquired traffic data, obtaining historical data of traffic loads of various devices of the hospital, and storing the data; the prediction module predicts future traffic loads of devices of the hospital based on historical data acquired in the traffic collection module and uploads the prediction result to the scheduling module; the application can predict future traffic loads of devices of the hospital, reasonably distribute network traffic to various data centers and corresponding servers according to the prediction result, flexibly configure the network, quickly adjust the distribution of network resources, and improve the medical experience of patients.

An object of a system according to an embodiment is to enable citizens to quickly find an optimal hospital in an emergency.SOLUTION: A system includes an input unit, an analysis unit, a selection unit, and a guide unit. The input unit inputs a medical history or a symptom of a user. The analysis unit analyzes the information input by the input unit. The selection unit selects an optimal hospital based on the information analyzed by the analysis unit. The guidance unit guides the shortest route to the hospital selected by the selection unit.SELECTED DRAWING: Figure 1

The application provides a resident medical treatment travel time calculation method and device based on a grid map, comprising the following steps: creating a time cost grid map of an area to be analyzed; obtaining location information of medical service institutions in the area to be analyzed, performing geographic coding to make the location information have latitude and longitude information, superimposing the location information on the time cost grid map, and forming a medical service institution spatial distribution data set; according to the time cost grid map and the medical service institution spatial distribution, using a minimum cost method to draw a medical service institution travel time map; and according to the medical service institution travel time map, obtaining a medical treatment travel time of each residential area in the area to be analyzed. The application can provide a reference for calculating the time of residents in different regions to different types of medical institutions, provide a basis for effectively formulating medical resource allocation policies, and increase the population coverage under different time thresholds.

The invention provides a hospital-infected infectious disease diffusion microscopic simulation method based on a contact network model, and the method comprises the steps: determining the influence space range characteristics of all people in a designated region of a hospital based on the activity data of people in the designated region of the hospital; accurate space dynamic calibration is carried out on the influence coverage range of secondary propagation possibly formed under the condition that each person is infected with infectious diseases; the method comprises the following steps: determining contact relation data among different persons based on respective influence space range characteristics of all persons in a specified area of a hospital, analyzing the contact relation data based on a propagation dynamics model, and determining propagation state information of infectious diseases among different persons; performing dynamic tracking and calibration on the real infectious disease infected persons in the designated area of the hospital; and then on the basis of the transmission state information, obtaining an infectious disease diffusion microscopic animation and personnel infection change characterization information of a hospital designated area, and dynamically displaying an infectious disease transmission change trend on a two-dimensional space level, thereby improving the prevention and control efficiency and accuracy of hospital-infected infectious diseases.

The present invention is applicable to the technical field of current status assessment and optimal design of traffic flow lines in the outdoor space of a building complex, and provides a quantitative analysis method for medical flow lines in the outdoor space of a hospital based on depth images and point cloud data. This method uses the external space status of the research site and patient-related data to conduct actual measurements of the congestion level, crowd movement speed information, crowd behavior activities, etc. of the established research site with a functional orientation, providing a more scientific and reasonable basis for the optimization and transformation of the site's traffic organization. This method proposes a method for quantitatively analyzing the medical efficiency of the space flow lines outside the hospital, and provides the best medical navigation route for in-hospital patients, laying a quantitative data foundation for the precise optimization of the traffic organization outside the hospital. A quantitative analysis and optimization method for traffic organization in the outdoor environment of the hospital is proposed for the research site, which is beneficial to promote the cross-development of planning and management of large and medium-sized hospitals in the city, and helps related site research to effectively improve medical efficiency and achieve the purpose of improving hospital service quality.

The invention relates to the technical field of intelligent medical treatment, in particular to a hospital-oriented intelligent scoring performance assessment method, system and device and a medium, and the method comprises the steps: obtaining the performance data of a plurality of hospitals, and extracting a standardized performance indicator vector; unsupervised clustering analysis is carried out on the standardized performance indicator vectors, multiple performance levels are divided, and benchmark groups are determined based on the performance levels; on the basis of the performance data of the benchmark group, key performance indicators and critical threshold values thereof are identified, and score weights are deduced through reverse regression analysis; constructing a scoring formula based on the key performance indicators, the critical threshold values and the scoring weights; and based on the performance data, calculating the comprehensive performance score of each hospital by using a scoring formula. According to the method, objective and adaptive scoring based on data driving can be realized, and scientificity and efficiency of hospital performance assessment are remarkably improved.

The invention discloses a hospital medicine collection task progress dynamic monitoring method and system based on an R language. The method comprises the following steps: acquiring an information table of selected collected medicines in all collected batches, constructing dictionary information of the collected medicines, extracting use data of the collected medicines, calculating a collected medicine completion progress, and performing analysis; based on the analysis result, further counting the completion condition of the drugs which do not reach the standard in the task of the collection batch in the current month in each department; and for the departments which do not complete the tasks, outputting R markdown report documents of progress early warning of drugs which do not reach the standards of the tasks. According to the method, the personalized analysis script is written based on the R language, the current-month use conditions of all the medicines executing the centralized collection batch in the hospital are comprehensively monitored, the task medicines and the completion progress of the department are automatically counted and analyzed, the data are visually displayed, the situation notification of the medicines which do not reach the standard in the department is generated, and the dynamic supervision of the use conditions of the centralized collection medicines is realized.

An object of a system according to an embodiment is to improve the effectiveness of telephone consultants by utilizing AI.SOLUTION: A system includes a symptom analysis part, an advice providing part, a hospital selection part, and a voice guidance providing part. The condition analysis unit receives telephone consultation from the user and analyzes the condition of the user. The advice providing unit provides advice based on the symptom analyzed by the symptom analysis unit. The hospital selecting unit selects a hospital based on the advice provided by the advice providing unit. The voice guidance providing unit provides voice guidance related to the hospital selected by the hospital selecting unit.SELECTED DRAWING: Figure 1

The system according to the embodiment aims to guide a user to an appropriate hospital based on the user's health condition. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, and a guidance unit. The reception unit inputs the user's health status. The analysis unit analyzes the information input by the reception unit. The guidance unit provides guidance to nearby hospitals based on the diagnosis results generated by the analysis unit.

The present invention discloses a hospital internal audit system and method based on drug management, and relates to the technical field of drug audit. The present invention sets an information summary unit to periodically collect and summarize and obtain drug summary information of a target hospital, sets a ciphertext interaction unit to convert drug summary data to obtain ciphertext audit data, wherein in the process of converting to obtain ciphertext audit data, a conversion logic is used to replace key encryption, thereby avoiding the risk of key loss and leakage, sets a drug audit module, stores the ciphertext audit data in ciphertext and sets plaintext access permissions, and temporarily restores the ciphertext audit data to automatically generate an audit report, and after the audit report is generated, the temporarily restored drug summary data is destroyed. In this way, the security of the ciphertext audit data before and after the audit is guaranteed, and the security of the audit result is further guaranteed.

The invention discloses an information recommendation method and device, computer equipment and a computer readable storage medium, relates to the field of computer networks, and aims to determine hospitals with low suitability and high compensation and eliminate the hospitals so as to recommend the hospitals according to the popularity, so that the medical suitability requirement can be met, and the compensation amount and the compensation risk can be reduced. The method comprises the following steps: acquiring a disease name and a doctor-seeing province and city name uploaded by a user based on a terminal held by the user, and querying a plurality of hospitals associated with the doctor-seeing province and city name; determining an adaptation index, a popularity index and a compensation label of each hospital in the plurality of hospitals for the disease name; inputting the disease name, the adaptation index corresponding to each hospital, the popularity index and the compensation label into a pre-trained elimination model, and identifying a to-be-eliminated hospital in the plurality of hospitals based on the elimination model; and obtaining an information recommendation result which is output by the elimination model and is generated based on the to-be-eliminated hospital, and sending the information recommendation result to a terminal held by the user.

The invention relates to the technical field of data security management, and relates to a hospital operation system based on storage encryption processing. Hospital operation data of all departments in a hospital are collected through a collection assembly, the operation data of all the departments are stored in a storage assembly, before storage, multiple pieces of operation data need to be encrypted through an operation assembly, and before encryption is executed, the multiple pieces of operation data need to be encrypted through an operation assembly. According to the method, encryption grade division is performed on each department in a hospital based on multiple hospital operation data through an operation component, so that a hospital storage encryption standard is created, and the storage encryption grade of each department in the hospital is updated in real time based on the hospital storage encryption standard. According to the method and the device, on the one hand, storage encryption of different means is carried out based on different department confidentiality levels, encryption means for operation data of low-level department confidentiality levels are reduced, encryption efficiency is improved, and on the other hand, safety of operation data of high-level department confidentiality levels is improved.

The present invention discloses a method and device for predicting the cost of medical service items based on key factors. The method includes: processing the basic information of medical service items based on the canonical correlation analysis algorithm to obtain the key factors of medical service items; inputting the key factors of medical service items into a pre-trained deep neural network model to determine the attribution of medical service items; predicting the cost of medical service items in each affiliated department according to the attribution of medical service items; and predicting the cost of medical service items in the hospital based on the cost of medical service items in each affiliated department. Through the canonical correlation analysis algorithm and the deep neural network model, while greatly improving the processing speed of relevant information, it can simplify the process of predicting the cost of medical service items. By predicting the cost of medical service items in each affiliated department and then predicting the cost of medical service items in the hospital, using a step-by-step prediction method is conducive to improving the accuracy of the prediction results.

The invention provides a disinfection and cleaning online registration method and system special for a hospital, and relates to the technical field of disinfection and cleaning management of the hospital, and the method comprises the steps: dividing the risk grade type of each disinfection region of the hospital based on the WS / T512-2025 regulation requirements, and obtaining region risk grade data; based on the regional risk level data, configuring corresponding exclusive registration dimensions and disinfection standards for each region, and generating regional disinfection configuration data; the method comprises the following steps: embedding regulatory core requirements into a system according to regional disinfection configuration data, and constructing a standard knowledge base; and obtaining an exclusive two-dimensional code based on the regional risk level data, the regional disinfection configuration data and the standard knowledge base. According to the invention, through the whole-process coverage of two-dimensional code configuration based on laws and regulations, code scanning linkage verification, classification and accurate traceability, and data-driven closed-loop rectification, standard, efficient and traceable management of disinfection and cleaning work is realized.

The invention relates to the field of medical information, and discloses an internet hospital weight management bidirectional referral triggering method based on hierarchical diagnosis and treatment, which comprises the following steps: comparing continuous physiological parameters, baseline data and a short-term risk score with a preset hierarchical diagnosis and treatment referral rule base; an upward referral suggestion is generated and pushed to a doctor end of the superior medical institution, and the upward referral condition includes that the short-term risk score exceeds a dynamic early warning threshold value or the duration that the continuous physiological parameters continuously exceed a preset red area threshold value reaches a preset first duration; or receiving a confirmation instruction based on the upward referral suggestion or the downward referral suggestion when the weight loss percentage is lower than a preset weight loss target value in a preset intervention period, calling a resource matching algorithm to determine a target medical institution, and generating an electronic referral sheet. According to the scheme of the invention, the congestion of the special number source of the three-first hospital is greatly relieved, and the long-trailing follow-up visit resource of the primary medical institution is activated.

The present application relates to the field of medical information technology, and provides a method and system for on-chain and off-chain interaction of hierarchical diagnosis and treatment data based on a consortium blockchain. In this method, after the patient signs the off-chain encrypted data generated by the lower-level hospital based on the patient's authorization using the patient's private key, the lower-level hospital generates on-chain plaintext data, and encrypts the generated on-chain plaintext data using the patient's public key to obtain on-chain ciphertext data; and re-encrypts the on-chain ciphertext data based on the proxy re-encryption key to generate a proxy re-encrypted ciphertext; stores the proxy re-encrypted ciphertext on the consortium blockchain based on the patient's pseudo-identity information, and transmits the signed off-chain encrypted data through the off-chain data channel; when the upper-level hospital passes the permission verification, the upper-level hospital obtains the proxy re-encrypted ciphertext from the consortium blockchain and decrypts it to obtain the on-chain plaintext data, and obtains the off-chain encrypted data from the off-chain data channel and decrypts it to obtain the patient's original diagnosis and treatment data for verification.

The system according to the embodiment aims to introduce a patient to an appropriate hospital based on the patient's symptoms and make an appointment. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, a prediction unit, a referral unit, and a reservation unit. The reception unit receives input of symptoms. The analysis unit analyzes the information received by the reception unit. The prediction unit predicts a disease based on the information analyzed by the analysis unit. The referral unit refers a patient to a hospital based on the disease predicted by the prediction unit. The reservation unit makes a reservation at the hospital referred to by the referral unit.

An object of a system according to an embodiment is to enable an applicant for a hospital consultation to quickly find an appropriate hospital on the basis of voice information and confirm acceptability.SOLUTION: A system includes a reception part, an analysis part, a retrieval part, a guide part, a communication part, and a confirmation part. The reception unit receives voice information. The analysis unit analyzes the voice information received by the reception unit and converts the voice information into text data. The search unit searches for a hospital based on the information analyzed by the analysis unit. The presentation unit presents a result of the search by the search unit. The communication part communicates the information guided by the guide part to the hospital side. The confirmation unit confirms acceptability based on the information notified by the notification unit.SELECTED DRAWING: Figure 1

The invention discloses a hospital full-process intelligent operation and maintenance command management system based on BIM Internet of Things cooperation, and belongs to the technical field of hospital management, and the system comprises a three-dimensional visual management module which is configured to establish a three-dimensional model of a hospital building, and carries out the display and management of the hospital building; the real-time monitoring acquisition module is configured to acquire hospital multi-source data; the preprocessing analysis module is configured to perform pre-diagnosis and preventive maintenance on hospital equipment faults; the intelligent operation and maintenance command management module is configured to perform automatic management on operation and maintenance activities; and the visual display interaction module is configured to provide an interaction interface to grasp the operation and maintenance condition of the hospital anytime and anywhere. The problem that intelligent operation and maintenance command management cannot be carried out on the whole process of a hospital based on BIM Internet of Things cooperation in the prior art is solved. According to the invention, intelligent operation and maintenance command management can be carried out on the whole process of a hospital, omnibearing digital management of hospital buildings and equipment can be realized, and powerful support can be provided for efficient operation and high-quality development of the hospital.

To provide guidance to a hospital and a doctor suitable for a patient in accordance with symptoms reported by the patient, and to provide an approximate time required until a medical consultation.SOLUTION: A patient support apparatus includes: symptom reception means that receives symptom report information and position information relating to one patient; provisional medical examination information extraction means that extracts provisional medical examination information associated with the symptom report information; medical consultation form extraction means that extracts medical consultation form information associated with the provisional medical examination information; hospital requirement extraction means that extracts facility information and specialization information associated with the provisional medical examination information; hospital extraction means that extracts hospital information satisfying the medical consultation form information, the facility information, and the specialization information; required time specification means that specifies a travel time for one patient to travel to each hospital on the basis of the position information and location information included in the extracted hospital information, and specifies a required medical examination start time being an approximate time until a medical examination is received at each hospital on the basis of the specified travel time; and hospital information provision means that provides the specified required medical examination start time for each hospital.SELECTED DRAWING: Figure 2

The invention relates to the field of medical artificial intelligence, and discloses a cross-hospital medical data adaptation system based on transfer learning, and the system comprises a field adaptive layer which encodes data of a source hospital and a target hospital and achieves the distribution alignment; a dynamic feature weight adjustment mechanism for dynamically calculating the feature weight of the target hospital based on the coding feature; continuously adapting to the optimization framework, carrying out online incremental learning and retaining historical experience, and providing updated parameters for a cross-hospital cooperative training mechanism; a cross-hospital collaborative training mechanism is adopted, and joint training and global model fusion are performed under the condition of keeping data privacy; and the multi-modal data fusion module is used for aggregating different modal data of multiple hospitals and transmitting the data to the field adaptive layer. According to the method, the field adaptive layer design based on the generative adversarial network is adopted, automatic alignment of data distribution of the source hospital and the target hospital is achieved, and manual intervention is not needed when the model is migrated among different hospitals by introducing multi-granularity feature coding and an adversarial discrimination mechanism.

The application discloses a kind of self-service equipment monitoring repair methods of wisdom hospital based on Internet of Things, and relates to Internet of Things technical field.The self-service equipment monitoring repair methods of wisdom hospital based on Internet of Things, based on the real-time monitoring information of each self-service equipment in target hospital, running basic information and extreme weather data analysis of the region where target hospital is located, obtain the fault monitoring early warning value of each self-service equipment in target hospital, judge the fault condition of each self-service equipment in target hospital;Based on the fault monitoring early warning value of each self-service equipment in target hospital, obtain the repair order of self-service equipment needing repair in target hospital;Based on repair order, the maintenance process of self-service equipment is tracked and recorded, and maintenance result is obtained;Whether the repair is qualified is judged by analyzing maintenance result, and secondary repair maintenance is carried out for unqualified repair condition;Real-time monitoring of various self-service equipment in hospital is realized, self-service equipment failure is found in time and repaired, and hospital operation cost and risk are reduced.

The present invention belongs to the field of medical health information technology, and provides a CKD high-risk factor screening system based on big data. The CKD medical record information of multiple CKD patients in a historical period is extracted from a hospital system through ETL technology, and analyzed to obtain high-frequency factors. The analysis is based on the high-frequency factors to obtain a preliminary screening high-risk factor table. The preliminary screening high-risk factor tables in multiple consecutive historical periods are analyzed and processed, and the ranking changes of high-frequency factors in multiple preliminary screening high-risk factor tables and the frequencies of occurrence in multiple consecutive historical periods are analyzed. The high-frequency factors are further screened to obtain sensitive factors, and the sensitive factors are summarized to obtain a sensitive high-risk factor table, so as to screen the factors of CKD patients layer by layer and determine the high-risk screening conditions, which is conducive to tracking and comparing all patients in the hospital according to the medical record information of the hospital patients, and improves the statistical efficiency of CKD patients.

The invention discloses a hospital resource scheduling method and system based on data analysis, and relates to the technical field of electric data processing, and the method comprises the steps: carrying out the task composition analysis processing of a task list of a hospital based on an intelligent control terminal, and determining the priority to-be-processed task of the hospital; and based on the intelligent control terminal, performing time analysis processing on the hospital priority to-be-processed task, and determining a hospital first to-be-processed task. The method comprises the following steps: firstly, analyzing a task list of a hospital server to determine a hospital priority to-be-processed task, and then comprehensively analyzing residual resources of the hospital server according to the completion time of the hospital priority to-be-processed task and resources required by the hospital priority to-be-processed task; and determining that the hospital server can complete the task in the specified time under the condition that the hospital server is not overloaded, and if the task cannot be completed, replacing the hospital server to complete the task, so that the overload condition of the hospital server can be avoided, and the task can be completed in the specified time.

The present disclosure relates to a method of operation of a server, wherein the method of operation comprises the steps of: obtaining event information related to a target area where the first terminal device is located from at least one first terminal device located within a hospital; selecting at least one second terminal device among a plurality of terminal devices located within the hospital based on the type of the obtained event information; and providing notification information to the selected second terminal device to correspond to the event information.

The invention relates to the technical field of diagnosis and treatment flow prediction, and discloses a hospital specialized diagnosis and treatment flow prediction method based on big data, and the method comprises the steps: carrying out the aggregation of hospital specialized flow data through employing a time window sliding mode, and obtaining the hospital specialized flow aggregation data of each time period; calculating the dynamic information gain of the flow index, and extracting the multi-layer diagnosis and treatment flow features by using the dynamic information gain of the flow index; and predicting the hospital specialized diagnosis and treatment flow by using the hospital specialized diagnosis and treatment flow prediction model. According to the method, the periodic window sizes of different flow indexes are generated in combination with the data distribution characteristics and the fluctuation degree, then the adaptive time window is generated, data aggregation is performed by adopting a time window sliding mode of the adaptive window size, the obvious degree of the periodic characteristics is improved, and the data aggregation efficiency is improved. The multi-layer diagnosis and treatment flow features representing the multi-layer features of the flow indexes are extracted, multi-layer time sequence analysis and prediction are carried out, and the flow prediction accuracy is improved.