300 results about "Patient identification" patented technology

Disclosed herein is urinary output monitoring system including a urinary collection device having a flow meter in communication with a monitor. The urinary collection device catheter includes a urine collection bag, a drainage tube and a urinary catheter. A console of the flow meter wirelessly communicates with a console of the monitor. The monitor depicts urine flow rate information on a display and wirelessly transmits urine flow rate information to an EMR system. The flow meter includes a flow meter identifier and the system links the urine flow rate information to the flow meter identifier. The monitor further links the flow meter identifier with a patient identification from the EMR system and depicts the patient identification on the display.

The present invention relates to the technical field of medical triage, and discloses an emergency patient triage system based on artificial intelligence, including: a data acquisition module: used to obtain the patient's identity and basic information by performing face recognition and fingerprint recognition on the patient, and receive health data uploaded by a wearable device, and transmit it to the patient's corresponding historical pathology library; a medical interaction module: used to provide an interactive platform for patients to remotely input pathological conditions based on 5G wireless communication technology; a multimodal data fusion module; a pathological feature matching module; a triage matching module; and a system integration and display module. Through the convolutional neural network model combined with pathological feature matching, based on the patient's question reply content, the condition and the judgment of the severity, a rapid judgment of the possibility of the disease, the generation of consultation content and the optimization of triage results are achieved, thereby improving the accuracy and efficiency of triage and reducing misdiagnosis and missed diagnosis.

The invention relates to the technical field of resource management, in particular to an operation resource allocation method and system, and the method comprises the following steps: integrating data of operation types, duration, equipment requirements and personnel requirements, combining the data with patient identity recognition information, creating an independent index, sorting the data into a queriable data set, and carrying out the data archiving processing, and obtaining a comprehensive resource data file. According to the method, dynamic adjustment of resources is effectively guided by learning historical data and predicting time distribution of equipment use frequency and personnel demands in resource management through a gradient elevator algorithm, the robustness and prediction accuracy of the model are improved through a random forest algorithm and an ensemble learning method, and the robustness and prediction accuracy of the model are improved. Therefore, the adjustment decision in the resource allocation process is more accurate, resource waste is reduced, the allocation efficiency of manpower and material resources is optimized, and the utilization rate of operation resources and the medical service quality are remarkably improved.

The invention discloses a pre-inquiry method based on a long and short term memory management large model. The pre-inquiry method comprises the following steps: S100, acquiring identity information and complaint symptom information of a patient; s200, establishing long-term memory and short-term memory corresponding to the patient; all information generated in the pre-inquiry dialogue process is stored in the short-term memory; the long-term memory and the short-term memory are updated and maintained based on a memory storage mechanism; s300, based on the long-term memory and the short-term memory, using a large model to construct multiple rounds of pre-inquiry dialogues, and obtaining patient condition information; and S400, summarizing the patient identity information, the complaint symptom information, the long-term memory and the short-term memory to generate a pre-inquiry report. According to the pre-inquiry method based on the long-short-term memory management large model, the long-short-term memory management is separated from the large model to carry out multiple rounds of pre-inquiry dialogues, the method does not need to depend on the memory ability of the large model, and the memory loss phenomenon in multiple rounds of dialogues commonly seen in an existing large model can be effectively avoided.

The invention relates to the technical field of digital data processing, in particular to an intelligent triage and guide analysis method, device and system based on a large language model.The method comprises the steps that symptom information of a patient is collected in a text input or voice input mode, and the symptom information and patient identity information are associated; cleaning the collected symptom information and extracting a symptom keyword group; matching the extracted symptom keywords with data in a knowledge graph to determine a to-be-selected disease group; generating a corresponding recommended department table according to the to-be-selected disease group, and arranging the departments according to the priority; and correcting the arrangement sequence of the departments based on the historical treatment records of the patients. Through the steps, the symptom information of the patient can be efficiently collected and processed, and accurate and personalized medical suggestions can be provided. According to the method, the efficiency and the quality of medical services are greatly improved, and meanwhile, the medical experience of the patient is also improved.

A system for bi-directional communication of patient data can include a first database having a first record including first data associated with a personal identification of a patient, a second database having a second record including second data associated with a user identification of the patient; and one or more processors configured to: pair the first data and the second data based upon a shared data item contained in the first record and the second record, and display a combination of the first data paired with the second data. A blockchain is used to paid the first and second records associated with different user identifications of the same patient.

A data command center visual display system presents dynamic data to a display screen. The command center visual display system includes a plurality of adjustable display panels configured to display predetermined combinations of patient identification information, patient insurance information, patient medical history information, a patient's insurance billing regulations, preferred practice patterns, and patient payment information, and a patient flowsheet that integrates the patient medical history information and patient payment information into a table that presents the patient's medical history by visit to one or more physicians with respective procedures or actions performed during each visit represented as icons identifying the procedure performed and icons indicating whether the procedure has been paid for in part or in full, the icons providing links to associated medical history data and / or financial data. The respective procedures or actions may also be activated directly from the table or display panels without leaving the display screen. In response to selection by a user of the visual display system, the adjustable display panels and patient flowsheet are moved into a task-based or specialty-specific display configuration such that the patient identification information, patient insurance information, patient medical history information, and patient payment information may be accessed without leaving the display screen.

The invention discloses a monitoring alarm system and method based on multi-modal fusion and regional perception, and the system comprises a multi-source perception module which collects the related data of a patient through a plurality of sensors; the data processing center is used for judging whether an abnormal state occurs or not based on the related data acquired by the multi-source sensing module, and triggering an alarm when the abnormal state occurs; and the notification terminal receives the alarm related information and executes alarm linkage measures. Wherein the data processing center realizes multi-modal data binding of the same patient by using the positioning identification module, so that the position of the patient is accurately positioned; the layered configuration module is used for setting alarm rules according to different patients and different areas. Multiple sensors are adopted for monitoring, the identity and state of a patient are accurately recognized through cross validation of multi-modal data, and the false alarm rate is reduced; a regional division monitoring strategy is adopted, excessive monitoring is avoided on the premise that the monitoring effect is ensured, and resource waste is avoided.

The invention discloses an emergency treatment high-risk patient real-time grading method based on an improved multi-mode Transform algorithm. The method comprises the following steps: S1, generating a time synchronization multi-mode event sequence; s2, obtaining a corresponding single-mode feature representation tensor; s3, obtaining a risk weighted cross-modal attention matrix; s4, in the improved multi-modal Transform fusion network, generating a fusion feature representation tensor by using a time sequence sliding window cache and incremental updating mechanism, and outputting a risk grading label and a corresponding risk grading confidence coefficient based on the fusion feature representation tensor; s5, inputting the risk grading label and the risk grading confidence into the interpretive sub-network, and generating clinical causal chain prompt information; and S6, synchronizing the risk grading label, the risk grading confidence and the clinical causal chain prompt information. According to the method, the accuracy of high-risk patient identification and the adaptability of the model to a clinical complex scene are remarkably improved, and a test result shows that the real-time identification accuracy of a high-risk case is improved compared with that of a conventional multi-modal model.

The invention discloses a patient information statistics system and method for an emergency department, and relates to the technical field of information statistics. A patient end is registered based on patient identity information, a storage unit is started based on the patient end, and the patient end is connected with the storage unit; the disease information of the patient is collected in real time, the disease information of the patient is stored in the corresponding storage unit, the bionic unit is derived according to the storage state of the storage unit, and the storage unit is replaced by the bionic unit. When unauthorized network access occurs, one bionic unit is started, a storage unit and other bionic units are transferred to another bit plane, if unauthorized network access still exists after transferring to another bit plane, one bionic unit is started again, and the storage unit and other bionic units are transferred again; therefore, the safety of the storage unit for storing the disease information of the patient can be ensured, the capability of dealing with unauthorized network access can be realized, and the safety of data is ensured.

The invention relates to the technical field of medical emotion early warning, and discloses an early warning system used based on a hospital platform. The system comprises a data acquisition module which is used for acquiring a patient identifier and treatment time, and acquiring voice dialogue and text record content and associated information to generate a patient data set; the sentiment analysis module is used for analyzing semantic and acoustic features of the voice and text contents and generating a sentiment analysis result set; the grading processing module is used for carrying out hierarchical division on emotions and generating a patient emotion grading result set; the information synchronization module is used for synchronizing the grading labels and the patient identifiers to a hospital information system display terminal according to specifications and generating grading information synchronization records; the intervention execution module is used for matching an AI automatic pacifying or manual intervention strategy for the patients higher than the basic warning level, and generating an intervention execution record set; and the early warning triggering module is used for marking the patient with the emotion activation risk and generating an early warning triggering result. The system can sense emotion changes of a patient in real time, active intervention is achieved, and the diagnosis and treatment order is maintained.

A patient engagement system comprises a database and various modules for communicating with health information systems and user mobile devices. An interface module of the system communicates with a health information system to receive patient information, such as patient registration information and patient medical information, therefrom. A user application module communicates with a user mobile device to receive user information, such as patient authentication information, therefrom. The database can store the patient medical information and user profiles of authenticated patients of the patient engagement system.

The invention relates to the technical field of medical care, in particular to a patient pressure sore recognition and nursing auxiliary system based on PDA and deep learning, and the system comprises PDA equipment which has a double-photographing function and is used for photographing a human face, uploading the human face to the system, inputting human face information, photographing a skin image of a patient and uploading the skin image; the server side is provided with a deep learning algorithm model and a nursing scheme database; the server side is used for analyzing the skin image of the patient uploaded by the PDA so as to judge the pressure sore condition; and the nursing scheme database provides corresponding scientific nursing measures according to the judgment result of the server side. According to the system, accurate pressure sore recognition is achieved by means of a deep learning algorithm and a thermal imaging technology, personalized nursing measures are generated by means of a nursing scheme database, accurate patient identity recognition is guaranteed by means of face recognition, medical risks are comprehensively reduced, and nursing efficiency and quality are remarkably improved.

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

The invention discloses a surgical site marking and verifying system based on multi-modal sensing and AI real-time checking, and belongs to the technical field of medical instrument management. The system comprises: a data acquisition module for acquiring a copy of preset surgical site data associated with a patient identity identifier; the intelligent marking pen comprises a pen point; the real-time checking module is used for checking whether a physical position of the pen point is consistent with a target area limited by preset surgical site data or not in real time when a proximity sensor detects that the pen point is located within a preset distance of the skin of a patient; the mark execution module is used for forming a physical mark in the target area under the condition that the verification result of the real-time verification module is consistent; and the multi-mode verification module is used for verifying the physical mark in the operation so as to confirm the consistency of the physical mark, the patient identity identifier and the preset operation site data. According to the invention, marking errors are avoided, and the problem that traditional marks are easy to erase is solved.

The invention discloses an integrated movable digital human interaction cooperation system and a method thereof, and belongs to the technical field of man-machine interaction, the integrated movable digital human interaction cooperation system comprises a mobile platform module, a central control module, an identification perception module, an information sharing access module, a crowd identification module and a user interaction module, the chassis system provides power to move, and the information sharing access module is accessed to an internal information network of a hospital through the Internet, receives internal related information of the hospital and transmits the information to the central control module and the crowd recognition module. According to the integrated movable digital human interaction coordination system and the method thereof, the functions of user interaction, hospital guide consultation, active patient identification, suspicious person marking, mobile platform integration, intelligent identification, information sharing and user interaction can be realized, the emergency response efficiency and the patient experience can be improved, and the practicability and the functionality are enhanced.

The invention provides a barrier-free AI intelligent guiding method. The barrier-free AI intelligent guiding method comprises the following steps: establishing a medical database on an AI intelligent cloud platform; the patient evokes the mobile phone APP through voice and records disease information and a doctor-seeing plan through the mobile phone APP, and the doctor-seeing plan reflects target doctor-seeing time and a doctor-seeing time period of the patient; the AI intelligent cloud platform receives the disease information, obtains an analysis result through an analysis strategy according to the received disease information, judges the disease condition according to the analysis result, generates initial diagnosis information, obtains a scheduling table through a matching strategy according to the initial diagnosis information, and sends the treatment information to the mobile phone APP and the AI hospital guide robot; according to the treatment information, the AI hospital guide robot corresponding to the strategy is matched, and the AI hospital guide robot timely arrives at a reception point for waiting according to the patient information; and after the patient arrives at the hospital, the AI hospital guide robot identifies the identity of the patient, acquires the treatment information of the patient, and realizes hospital treatment navigation.

The invention belongs to the technical field of health management, and particularly provides a hospital health management early warning method based on body temperature data, which comprises the following steps: collecting body temperature data of a patient in real time through a body temperature monitoring device deployed on the body surface of a clinical patient and / or a monitoring area, and comparing the body temperature data with a preset threshold range; when the body temperature data of at least one patient exceeds a preset threshold range, generating a warning signal containing an abnormal body temperature value, a timestamp and an equipment identifier, and sending the warning signal to the control terminal; the control terminal analyzes a position information source of the warning signal based on the equipment identifier, and calls electronic medical record information of a patient corresponding to the position; according to the abnormal body temperature value, the position information and the medical record information, generating a control signal comprising a patient identity label, an abnormal body temperature tendency chart and suggested medical measures, and sending the control signal to a mobile terminal of a specified medical worker; real-time continuous monitoring and automatic early warning response of the body temperature of a clinical patient are achieved, and the discovery and treatment timeliness of abnormal body temperature events is remarkably improved.

To provide a medication history management apparatus with which a highly accurate medication history is registered and utilized.SOLUTION: A server includes a communication unit, a storage unit, and a control unit. The communication unit receives, from a patient terminal, which is a terminal of a patient, a drug image which is an image of drugs captured when the patient takes them. The storge unit stores the drug image received by the communication unit in association with patient identification information identifying the patient, the date of medication, and the time of medication. The control unit reads, from the storage unit, in accordance with a request from a health worker terminal which is a terminal of a dispensing pharmacy or a hospital, medication history data in which the drug image, the date of medication and the time of medication are associated with each other, corresponding to the patient identification information received from the health worker terminal, transmits the data to the health worker terminal, and displays a medication history screen in which the drug image, the date of medication and the time of medication are associated, on the health worker terminal.SELECTED DRAWING: Figure 5

An electronic patient monitoring system and method of operation that includes one or more generally non-metal, tamper-resistant patient identification and monitoring devices, an observer transmitter / receiver device configured to receive and detect one or more beacon signals that exceed a predetermined threshold from at least one of the not easily removable patient identification and monitoring devices, set a time to hold open a window for a response on the transmitter / receiver device, and send a request for information to the observer with the transmitter / receiver device, and a central computer system. Each of the transmitter / receiver device and the central computer system, including, at least, a computer processor, communications components and system software to communicate with the observer transmitter / receiver device at specified / predetermined time intervals to receive observer-and patient-specific information.

One embodiment provides a method including transmitting a pick-up request to transport a patient within a healthcare facility. The method includes receiving an acceptance indication for the pick-up request that has an associated handoff protocol that is based upon a condition of the patient. The method includes generating a patient identification request requesting a scan of an identification tag of an individual. The method includes receiving image data and determining whether the image data includes an image of the identification tag. The method includes verifying an identity of the individual. Other aspects are described and claimed.

The invention relates to the field of intelligent medical treatment, and discloses a hospital integrated platform system based on artificial intelligence, which comprises the steps of extracting current patient identification information, identifying a surgical patient in an anesthesia state in real time, and automatically associating a preoperative electronic medical record with an intraoperative anesthesia plan; based on an artificial intelligence semantic recognition model, performing image character extraction and semantic understanding on parameter contents set in real time in a respirator equipment screen; constructing a cross-system risk factor graph according to the semantic difference between the set parameters and the system identification, and performing risk linkage scoring on the operation behavior in the operation in real time; calling a parameter evolution path under the previous similar operation mode, and carrying out analogy modeling by combining the anesthesia depth of the current patient, the physiological data and the intraoperative stage; and when it is confirmed that strategy level abnormity exists in the setting, the early warning level and the display form are dynamically adjusted based on the operation equipment type, the setting personnel role and the load intensity of the current stage. The system has the advantage of improving the intelligent level of a hospital.

The invention discloses an inquiry diagnosis and treatment and examination treatment suggestion method and device based on an information updating management mechanism and a storage medium. The method comprises the steps that patient identity information is acquired, and patient diagnosis and treatment information is acquired; establishing multiple rounds of inquiry dialogues, wherein the process comprises the following steps: initiating a first round of inquiry dialogue question; extracting patient condition information based on the patient answer information, and extracting associated information related to the patient condition information from the patient diagnosis and treatment information; summarizing the patient condition information and the associated information to obtain patient inquiry information; dividing patient inquiry information into long-term memory information and short-term memory information, and updating and maintaining based on an information updating management mechanism; calling the large model to give inquiry diagnosis and treatment based on the inquiry information of the patient, judging whether the inquiry is finished or not, and if not, obtaining a next round of inquiry dialogue problem through the large model; if yes, the large model gives final inquiry diagnosis and treatment, and the final inquiry diagnosis and treatment comprise examination and treatment suggestions. Therefore, historical diagnosis and treatment information of the patient is fully utilized, and inquiry accuracy and efficiency are improved.

Each medical site visited by a patient stores the patient's clinical data in a local database, indexed by a site-specific pseudo-ID (SPID) assigned to the patient, such as a patient number or other identifier. A Patient Data Directory System (PDDS) is provided to facilitate access to the clinical data of the patient at each medical site. As each medical site stores the patient's clinical data, a set of metadata is provided to the PDDS that identifies where the clinical data is stored at the medical site, as well as the SPID used at the particular site. This metadata is entered into the PDDS, and can be used to retrieve the clinical data stored at each medical site. Access to the PDDS is controlled by the patient, thereby enabling the patient to provide some or all of the metadata required to access the patient's clinical data to select clinicians. A variety of cryptographic protocols are used to prevent unauthorized access to the patient's data.

The invention provides a drug tracing information automatic acquisition method based on two-dimensional code recognition, and the method comprises the steps: obtaining drug batch information and a subpackage record, and generating a dynamic tracing label which comprises a batch number, subpackage time and a subpackage number; extracting a medication cycle and a medicine validity period from the patient-level traceability identifier, identifying a matching degree of non-uniform validity period distribution and time window overlapping according to the medication cycle and the medicine validity period, and determining a medication cycle distribution scheme of the subpackaged medicine; according to the medication cycle distribution scheme, the medication demand and the medicine flow data of the patient are recognized, a dynamic flow record containing the identity of the patient, the subpackage time deviation and the medication time is generated, and medicine flow tracking information after information granularity is reduced is obtained; and according to the adverse reaction traceability report, updating the dynamic traceability label in the block chain, and generating optimized traceability data with reduced information granularity.

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.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for creating source-specific, persistent patient identifiers for healthcare service providers. One method includes accessing a record of healthcare data, wherein the record includes patient identifying information (PII) associated with one or more persons to whom the healthcare data pertains. The portions of PII included in the accessed record of healthcare data are extracted from the accessed record and encrypted. Based on one or more business rules, one or more hashed tokens are created by applying one or more hashing functions to the extracted portions of PII. A source-specific identifier is received, the source-specific identifier having been encoded in a manner specific to an organization associated with the computer system and having been encoded with reference to the one or more hashed tokens. An association is stored between the source-specific identifier and the accessed record of healthcare data.

Automatically generating a structured medical note during a remote medical consultation using machine learning. A provider tele-presence device may receive audio from a medical provider. A medical documentation server may be coupled to the network. A machine learning network receives audio data from the provider tele-presence device, the machine learning network generating a structured medical note based on the received audio data, and wherein the structured medical note is stored in the medical documentation server in association with an identity of a patient.

The invention discloses an intelligent wheelchair scheduling method and device, equipment and a medium, and relates to the technical field of computers, and the method comprises the steps: building an automatic synchronization mechanism with an internal system of a hospital, and obtaining check list task data from the internal system of the hospital based on the automatic synchronization mechanism; screening the to-be-dispatched intelligent wheelchair, generating an intelligent wheelchair dispatching instruction, and sending the intelligent wheelchair dispatching instruction to the to-be-dispatched intelligent wheelchair, so that the to-be-dispatched intelligent wheelchair executes the intelligent wheelchair dispatching instruction and moves to a target position; acquiring patient identity information at the target position sent by the to-be-scheduled intelligent wheelchair, verifying the patient identity information, and if verification succeeds, generating and sending an inspection instruction to the to-be-scheduled intelligent wheelchair based on the inspection list task data, so that the to-be-scheduled intelligent wheelchair transports a patient to an inspection site according to the inspection instruction. According to the invention, the patient examination efficiency can be improved, the patient examination complexity is reduced, human resources and equipment are reasonably utilized, and the overall operation efficiency of a hospital is improved.

The embodiment of the invention provides an intensive care data acquisition method and system, which can solve the problems of alarm fatigue, low equipment management efficiency and data islanding existing in an ICU environment for a long time. The method comprises the following steps: receiving a Bluetooth broadcast data packet reported by a plurality of Bluetooth gateways deployed in an ICU ward, wherein the Bluetooth broadcast data packet comprises Bluetooth Beacon signals periodically broadcasted by bed unit Bluetooth tags configured by a plurality of sickbed units and low-power-consumption Bluetooth broadcast signals from a plurality of Bluetooth converters; performing position estimation on each Bluetooth converter based on the Bluetooth broadcast data packet, so as to automatically bind the medical equipment and the bed units according to the spatial position relationship between the Bluetooth converters and each bed unit; and when the equipment monitoring data from the Bluetooth converter is received, associating the equipment monitoring data with the patient information of the corresponding bed unit, and generating a structured monitoring data record with the unique identification of the bed unit, the patient identification and the medical equipment identification.