115 results about "Patient identification" patented technology

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 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 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 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.

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 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.

A method for patient identification comprises the steps of: determining (S10) initial identification data during an initial measurement of a patient (P) using a first measuring device (1) for determining ophthalmic and / or optometric measurement data; and determining (S30) a patient ID of the patient based on the determined initial identification data. The invention also relates to a system or computer program (product).

The invention discloses a patient medical health joint decision-making system, and the system comprises a patient terminal which is used for carrying out the medical health interaction of a patient with a doctor terminal; the dialogue system is used for performing dialogue with the patient through the patient terminal according to a friendly dialogue mode which is easy to understand the patient condition so as to obtain the current patient condition and patient identity information; the patient historical data aggregation device is used for collecting patient historical medical information, including treatment and examination information, of the patient according to the patient identity information; the auxiliary decision-making system is used for generating a plurality of patient auxiliary medical schemes according to the patient historical medical information and the patient current illness state collected by the patient historical data aggregation device; and the doctor terminal is used for making a patient preliminary diagnosis and treatment scheme by a doctor according to a plurality of patient auxiliary medical schemes from the auxiliary decision-making system, interacting with the patient through the patient terminal, and jointly making decisions, so that the medical effect of the patient can be ensured, and the patient can also satisfy and accept the medical scheme.

This disclosure proposes a medical network image processing method and apparatus. In response to acquiring a pathological image to be processed, the method extracts a mask region of the pathological image to be processed. Since the mask region represents the region of the patient's identity features corresponding to the pathological image to be processed, a pre-trained adjustment model is used to adjust the mask region corresponding to the pathological image to be processed. The resulting target privacy-preserving image only adjusts the region of identity features and does not adjust other regions. While removing the patient's identity information, the relevant pathological features in the pathological image are preserved.

A patient access amount intelligent recording method, device and equipment and storage medium, comprising: scanning the patient identity carrier through the identity recognition module of the handheld intelligent terminal to obtain the patient identity information; receiving the access amount type information input by the user through the type selection interface of the handheld intelligent terminal; collecting the weight data of the measured object through the intelligent weighing device wirelessly connected with the handheld intelligent terminal and sending to the handheld intelligent terminal; converting the weight data into volume data according to the preset physical quantity conversion rule through the data processing module of the handheld intelligent terminal, combining the patient identity information to generate the access amount record; and sending the access amount record to the medical information system for storage, solving the technical problems of tedious operation steps, low efficiency and data recording errors caused by the existing manual operation mode, and realizing the simplification of operation steps to improve the work efficiency and accuracy.

Patient identification is transmitted to a health care provider prior to the patient arriving at the health care provider. The patient identification may be a driver's license, health insurance card, or other identification, and may be used to pre-register the patient. The transmission may include other information, such as health status, purpose of visit, intended procedures, symptoms, or other information. The transmission may be made via a device, such as a cellular telephone, where the information may be encrypted and transmitted using a secure mechanism. The system may be used by ambulance personnel, paramedics, or other emergency responders to notify a hospital, for example, of an inbound patient, as well as by patients prior to an appointment. The system may also be used by clinicians or other health care providers to prepare for emergent or non-emergent patients prior to arrival.

The application discloses an electronic medical record connotation quality control method and device based on diagnosis and treatment thought chain. The method comprises the following steps: first, acquiring electronic medical record data and performing standardization processing to obtain standardized data containing patient identification, diagnosis information, medical order information and the like; based on a pre-constructed hierarchical diagnosis and treatment thought chain knowledge graph, integrity, logicality and timeliness verification is performed on the standardized data through a rule engine, a bidirectional reasoning engine and a time window; three types of verification results are aggregated to generate a quality control report, and the report contains quality scores, problem details and reasoning path visualization data. The knowledge graph of the application contains a core general layer and a special plug-in layer, covers multiple types of diagnosis and treatment nodes and relationships, can accurately identify deep logical contradictions and timeliness problems of medical records, provides transparent and interpretable quality control results, and significantly improves the accuracy and clinical practicability of medical record connotation quality control.

Disclosed are computer-implemented methods which encompass determining whether two medical images were taken of the same patient. In a first aspect, this is done by analysing a registration of the two images with one another. The registration may be a direct registration between the two images or an indirect registration, for example via an atlas to which each image is registered. In other aspects, a machine learning algorithm is trained on the basis of image registrations to determine whether the two images were taken of the same patient. The disclosed methods serve the purpose of being able to group medical images together which were taken of the same patient without having to provide or otherwise process data about the identity of the patient.

There is obtained a cheek retractor that a right outer flange and a left outer flange are provided with a right personal authentication identification code plate portion and a left personal authentication identification code plate portion, respectively, on which two-dimensional barcodes are printed. Since the cheek retractor is mounted on an oral cavity of a patient by holding an arm, which is close to the right personal authentication identification code plate portion and the left personal authentication identification code plate portion, by hand and by pushing the arm inward against a spring force, and an image including a right personal authentication identification code and a left personal authentication identification code is captured, even without experience, an image can be captured to encompass the entirety of a mouth, and since identification information of the patient can be acquired, who the patient is can be grasped.

This invention discloses a multi-channel infusion volume monitoring terminal and an intelligent infusion stand management system. The monitoring terminal integrates multiple sets of electromagnetic induction sensors to simultaneously detect the remaining fluid volume of multiple infusion bags, and combines this with an RFID identification module to automatically identify patient information. The control module within the terminal executes a multi-channel isolation algorithm on the sensor signals to eliminate electromagnetic interference between adjacent channels and accurately calculate the remaining volume of each infusion bag. When a bag of fluid is nearly empty or the infusion is abnormally interrupted, the terminal's audible and visual alarm module immediately triggers an alarm and locates the abnormal infusion bag via a corresponding indicator light. Simultaneously, the terminal can transmit monitoring data and alarm information to the central monitoring device at the nurse station via a wireless network, enabling centralized real-time management of multiple patient infusions. This invention improves the automation and safety of batch infusion monitoring, reduces nurses' workload, and has advantages such as compact structure, accurate monitoring, and wide applicability.

The invention discloses a deep learning-based lung cancer adjuvant chemotherapy benefited patient identification method and system, and relates to the technical field of lung cancer precise treatment and artificial intelligence crossing, and the method comprises the steps: analyzing and preprocessing preoperative and postoperative registration logs of a patient to obtain basic information of the patient, a pathological image of the patient and a treatment strategy of the patient; the method comprises the following steps: performing segmentation processing on a patient pathological image by adopting nnformer to obtain a focus region segmented image, performing feature extraction and enhancement on the focus region segmented image to obtain image omics features, and constructing an improved 3D survival analysis model; and analyzing the basic information of the patient, the radiomics characteristics and the treatment strategy of the patient by adopting an improved 3D survival analysis model to obtain an identification result of the lung cancer adjuvant chemotherapy benefited patient. According to the method, the quantitative survival risk score and the adjuvant chemotherapy sensitivity conclusion are output, and an interpretable reference basis is provided for clinical decision making.

The invention relates to the technical field of patient skeleton X-ray image recognition, in particular to an image processing-based latent fracture auxiliary recognition method. And positioning a skeleton region and a soft tissue region connected with the skeleton region in the X-ray image. Selecting a reference skeleton area, and evaluating the fracture expression degree by analyzing similar gray pixel distribution and edge positions of the reference skeleton area; and for the soft tissue region, calculating the necessary degree of soft tissue enhancement according to the gray difference between the soft tissue region and the peripheral tissue, the gray difference between the two internal regions and the distance between the soft tissue region and the skeleton. And determining the necessary degree of bone enhancement according to the number of the soft tissues connected with the bone, the necessary degree of enhancement of each soft tissue and the fracture expression degree. And screening a to-be-enhanced area to perform image enhancement, and finally realizing accurate identification of the occult fracture. According to the invention, extremely small bone trabecula structure disorder or density change can be detected, so that the patient identification accuracy of related personnel is improved.

The invention relates to the technical field of artificial intelligence medical treatment, in particular to a patient value and loss risk assessment system and method based on combination of ML and LLM. The patient value and loss risk assessment system comprises a data acquisition module, a feature construction module, a model training module, a high value prediction module, a loss risk assessment module, an interpretability module, a result linkage module and a model iteration module. The data acquisition module is used for acquiring historical and real-time multi-source medical data of a patient; the feature construction module is used for integrating the acquired data of the data acquisition module to generate a multi-modal feature vector; a double-model cooperative training architecture is adopted, an ML model accurately captures a nonlinear relationship of numerical features, an LLM model deeply analyzes semantic information of text data, and the advantages of the two models are complementary, so that the utilization efficiency of multi-modal medical data is effectively improved, and a high-value patient identification and loss risk prediction result better fits clinical practice.

The invention relates to multi-channel breathing nursing monitoring equipment, which belongs to the technical field of medical instruments, and comprises a multi-channel gas sampling module, which is used for collecting and shunting gas exhaled by a patient through a shunting tube and a shunting tube connecting seat, so as to prevent cross infection; the independent mechanical sampling device is used for quantitatively sampling the shunted gas; the sensor group is used for carrying out multi-parameter detection on sampled gas; the two-dimensional code generation module integrates the sensor data and the patient identity information to generate a two-dimensional code; the data processing unit analyzes and processes the two-dimensional code information; the two-dimensional code recognition module recognizes and restores the data; and the data storage and display unit stores and displays the breathing data of the patient. All the modules work cooperatively, accurate monitoring and management of breathing data of a patient are achieved, accurate breathing data are provided for medical staff, the efficiency and quality of breathing nursing are effectively improved, and breathing treatment and rehabilitation of the patient are assisted.

The invention relates to the field of medical documents, and discloses a medical document writing assistant comprising an end interaction module which constructs a graphical user interface through Python-tkinter, is used for receiving patient identity information and document time range instructions input by medical staff and displaying the generated medical documents, and is in butt joint with a hospital heterogeneous information system through an HL7FHIR standard interface, so that the medical documents can be written in the hospital; and medical data of the specified patient in the corresponding time range is acquired in a sending mode, wherein the medical data comprises an inspection result, an image diagnosis report, a doctor's advice record and vital sign data. Clinical dilemma is broken through full-process automatic design, a front-end interaction module quickly receives an instruction, a data acquisition and standardization module concurrently calls multi-system data based on an HL7FHIR standard, and serial waiting is avoided; the intelligent processing module automatically completes data structuring through a regular expression and a medical pre-training model, the document generation module dynamically fills content based on a template, a standard document can be generated within several seconds, and the efficiency is improved by dozens of times compared with manual efficiency.

A system for a dysphagia patient 100 includes: an information acquisition unit 10 that acquires patient identification information 30 capable of identifying a patient and bed angle information 31 of the patient's bed 6 based on the patient's swallowing function; a storage unit 11 in which the patient identification information 30, location information 32 indicating one of an address of the bed 6, an address of a display device 3 installed in a location visible from the bed 6, and the patient's whereabouts, and the angle information 31 are stored in association with each other; and a control unit 12. The control unit 12 uses the patient identification information 30 to acquire the location information 32 and the angle information 31 associated with the patient identification information 30 from the storage unit 11, and uses the location information 32 to transmit the angle information 31 to at least one of the bed 6, the display device 3, and an information terminal 8 held by a caregiver for the patient's meal.

The invention relates to the technical field of psychiatric medical equipment, and discloses a mental patient medicine taking intelligent checking system and method based on an image recognition technology. The system comprises a facial feature acquisition module, a medicine identification module, a medicine taking action capture module, a data fusion module, a medicine taking compliance analysis module, an abnormal behavior identification module, an intervention instruction generation module, a medical care alarm module and a medicine taking record updating module. The medicine recognition module generates medicine contour feature points to check medicines; the medicine taking action capture module captures hand movement tracks; the data fusion module aligns the three parts in a space-time manner; the medicine taking compliance analysis module compares action compliance; the abnormal behavior recognition module recognizes abnormal swallowing actions, the intervention instruction generation module generates grading intervention signals, the medical care alarm module triggers corresponding alarms, and the medicine taking record updating module updates the electronic medicine taking archive when medicine taking is compliant.

The invention discloses an acute and critical symptom data mobile management system. The system comprises a data acquisition module, a data transmission module, a data storage module and a data query module, the invention also discloses an acute and critical symptom data mobile management device. The device comprises the cloud platform and hospital terminal equipment. According to the system, the data acquisition module is added, unique identification information and related medical record data of each acute and critical patient are acquired through hospital terminal equipment, and then the acquired data are uploaded to a cloud platform of the data storage module through the data transmission module; the data storage module is used for storing the acquired unique identification information and related medical record data of the acute and critical patients based on the block chain; then, a data query module is added, the data query module allows different hospital terminal devices to pass patient identity recognition, and the historical medical record data, stored based on the block chain, of the patient can be queried without carrying medical records by the patient.

The application discloses a time axis key node automatic acquisition system for chest pain diagnosis and treatment, relates to the field of information and communication technology of medical data, and comprises a pre-stored interval template containing starting or ending anchor point rules; an event stream carrying chest pain patient identification and source system time stamp derived from one or more medical information systems is acquired in real time; an active interval instance in memory is created and maintained for the chest pain patient; a candidate ending event is inferred; source system time reference drift is identified, and a reliability label is attached to time-consuming data. The application realizes automatic and real-time monitoring of the time consumption of the diagnosis and treatment process. The system not only supports starting and ending anchor point matching, automatically identifies time reference drift and attaches a reliability label, but also guarantees the reliability of time-consuming data in a real complex environment without relying on strict time synchronization of the whole hospital system.

Disclosed are computer-implemented methods comprising determining whether two medical image acquisitions are of the same patient. In a first aspect, this is done by analyzing the registration of the two images to each other. The registration can be a direct registration between the two images, or an indirect registration (e.g. via an atlas to which each image is registered). In other aspects, a machine learning algorithm is trained based on image registrations to determine whether two medical image acquisitions are of the same patient. The disclosed methods are aimed at enabling medical images taken of the same patient to be grouped together without the need to provide or otherwise process data regarding the identity of the patient.

The invention discloses a nerve-mediated syncope risk prediction method and system, and relates to the technical field of medical evaluation.The method comprises the steps that firstly, units are divided according to patient identity types and syncope scenes in a two-dimensional mode, and then a scene-syncope association model is constructed according to historical syncope records; through multi-dimensional data acquisition, matching of inducement features corresponding to user identity types, locking of associated suspicious syncope scenes, prediction of the risk of user syncope, when the risk exists, intervention measures are provided for the user, the intervention condition is monitored, and corresponding feedback is carried out at the same time, the method can identify multiple syncope scenes and multiple identity types, and the safety of the user is improved. The collaborative risk is quantified, the accuracy of risk level judgment is guaranteed, the prediction precision is greatly improved, early-stage and high-accuracy risk prediction is achieved, scene-identity-intervention association rules are established, the individuation and pertinence of intervention measures are improved, the intervention effect is guaranteed, and therefore the safety of a user is improved.

The application belongs to the technical field of medical information processing, and discloses an emergency patient condition dynamic evaluation method based on a mobile terminal. A patient identification, a priority weight and a condition baseline feature vector are encapsulated in a queuing two-dimensional code by acquiring patient triage results and baseline sign data. Queuing information and the baseline feature vector are obtained by scanning the code with a mobile terminal, and qualitative clinical observation information collected by nurses is converted into a quantitative offset value based on a clinical observation semantic knowledge base. The quantitative offset value and the baseline feature vector are subjected to offset amount operation, and a condition deterioration risk index is calculated in combination with queuing duration, triage level and queuing environment. The just-visit priority weight is dynamically adjusted according to the condition deterioration risk index, and a queuing sequence is reconstructed, which is reordered in an emergency information system and a change notification is pushed to related patients and clinics. The application provides high-quality technical support for emergency queuing management and intelligent triage.

To efficiently acquire historical images suitable for current image analysis in a short amount of time. [Solution] The medical information processing device according to the embodiment includes: a first information acquisition unit that acquires patient identification information and current image information including the current image; a database inquiry unit that searches an analysis result generation information database using the patient identification information as a search key to acquire examination identification information and series identification information which are past images of the patient indicated by the patient identification information and are associated with past images used in previous analysis processing; and a second information acquisition unit that acquires past image information which includes past images belonging to the series indicated by the series identification information from among the medical images taken in the examination indicated by the examination identification information.

The application discloses a thyroid cancer and neck lymph node metastasis risk assessment method, relates to the cross technical field of bioinformatics and metabolomics, and mainly comprises the following steps: converting single-cell metabolomics signals into a metabolic feature matrix with cells as rows and metabolites as columns, constructing a patient-level metabolic dataset based on patient identification information, preprocessing the patient-level metabolic dataset to obtain a preprocessed patient-level metabolic dataset, screening features to obtain key metabolic features, and performing hierarchical summary prediction to obtain individual risk assessment results. The thyroid cancer and neck lymph node metastasis risk assessment method can non-invasively and accurately predict the risk of thyroid cancer and neck lymph node metastasis.