168 results about "Triage" patented technology

The present invention provides a multilingual, AI-powered healthcare system integrating a personalized medical assistant, real-time clinical decision support, and closed-loop device control. The system ingests multimodal patient-generated and institutional data, applies advanced language-model-driven reasoning for clinical insights and triage, and supports regulated, auditable actuation of medical devices. Key features include multilingual overlays, role- and jurisdiction-specific visualization, co-signature enforcement, audit traceability, and seamless integration with healthcare infrastructure. A “Multilingual Overlay” is a dynamically generated display layer that the system composites in real-time from clinical text, icons, and color-coded indicators, automatically adapting its language, reading direction, terminology, visual density, and role-based data visibility to the preferences, locale, and device form-factor of each authenticated viewer. The architecture supports provider- and patient-facing use cases, agentic AI for autonomous yet regulated decision-making, and robust safety and compliance features.

The invention belongs to the technical field of medical health management, and particularly relates to an AI personalized health education system for elderly patients with head and neck cancer, which comprises a content generation and management module, a personalized push engine, an interaction and artificial triage module, an elderly friendly interaction module and a data monitoring and safety module, by adopting an AI + manual hierarchical response mechanism and combining elderly friendly interactive design and operation training support, the participation obstacles that elderly patients are inconvenient to move and poor in informatization ability are broken through, and the intervention compliance and sustainability are improved; according to the intervention method, strict double-group random control test design is adopted, multi-dimensional and multi-time-point effect evaluation is combined with a scientific statistical analysis method, the improvement effect of AI-assisted health education on cancer recurrence, fear, psychological state and life quality of a patient can be accurately verified, and a solid evidence-based basis is provided for clinical popularization.

The invention discloses an internet hospital hierarchical diagnosis and treatment and resource scheduling method and system, and the method comprises the following steps: responding to a diagnosis and treatment request sent by a user, and obtaining diagnosis and treatment data containing the chief complaint information of a patient; inputting the diagnosis and treatment data into an illness state evaluation model for feature extraction, and outputting a feature vector representing the illness state of the patient; the feature vector at least comprises a first dimension parameter representing an emergency degree of an illness state and a second dimension parameter representing a complexity degree of the illness state; determining a target resource node in a hierarchical medical resource database based on the feature vector; and generating a resource scheduling instruction according to the target resource node, and establishing a communication link between the user terminal and a server corresponding to the target resource node. According to the method, a two-dimensional evaluation system of urgency and complexity is introduced, and a dynamic threshold adjustment mechanism based on supply and demand prediction is combined, so that the utilization efficiency of medical resources and the accuracy of triage matching are remarkably improved.

The invention discloses an intelligent outpatient service guidance and triage management method and system based on artificial intelligence. The method comprises the following steps that patient information, symptoms and outpatient service data are collected to generate triage input; constructing a triage optimization model based on the input, setting waiting time, path cost, load rate and priority satisfaction degree as targets, and setting a time window, resources and dependency constraints; an improved squirrel search algorithm is initialized, a population code is adopted to represent a distribution scheme, and a fitness function is established; updating the candidate scheme according to a fitness function in iteration; repairing and locally optimizing the updating scheme; when the operation data fluctuates, self-adaptive adjustment is triggered, and updating is continued; and when the fitness function converges or the iteration upper limit is reached, outputting an optimal triage scheme, including departments, time windows and path allocation, and executing incremental optimization when the patient arrives or the shift arrangement is changed. The triage efficiency is improved, the load is balanced, and the requirements of priority patients are met.

The invention provides a robot hospital guide method based on multi-modal data and an intelligent hospital guide robot, and relates to the technical field of robots. The intelligent hospital guide robot comprises a multi-mode sensing module, an intention understanding and decision center module and a behavior execution and guide module. The method is applied to the intelligent hospital guide robot, and comprises the following steps: collecting multi-modal data through a multi-modal sensing module; performing information fusion and intention understanding on the acquired multi-modal data through an intention understanding and decision-making center module, and generating a decision-making instruction; executing a decision instruction through a behavior execution and guidance module, so as to execute personification interaction by controlling joint movement of the intelligent hospital guide robot and / or execute visual guidance by rendering and superposing an augmented reality navigation arrow on a display screen of the intelligent hospital guide robot; the problems of unfriendly interaction, single perception, rigid planning and the like in the prior art are solved, and the triage accuracy, the user experience and the adaptability in complex medical scenes are remarkably improved.

The invention provides an intelligent triage method and system for outpatient and emergency treatment, and relates to the technical field of medical information. The method comprises the steps that physiological data, symptom description text data, facial image data and voice audio data of a patient are collected through a multi-mode sensor; analyzing the image and audio data by using an emotion calculation engine to generate emotion state data; processing the physiological and text data through an analysis model to generate illness state emergency degree data; fusing emotion and illness state data to form a preliminary triage result; in combination with the real-time medical resource state data, a triage decision-making scheme including department allocation, processing priority and personalized pacifying strategies is generated through a dynamic decision-making device; finally, guiding and pacifying are executed through the execution terminal and the interaction robot, automation, intelligence and humanization of the triage process are achieved, the triage efficiency and accuracy are remarkably improved, medical resource configuration is optimized, and care for psychological needs of patients is enhanced.

The present invention discloses a system and method for healthcare diagnostics using foundation models with uncertainty triage, designed to deliver reliable, explainable, and safety-assured diagnostic outcomes across multimodal clinical data. The invention integrates a foundation model processor pretrained on diverse medical datasets with an uncertainty estimation processor configured to quantify epistemic and aleatoric uncertainties in diagnostic predictions. A triage control unit dynamically classifies cases into high, medium, and low-confidence categories based on computed uncertainty indices, ensuring that only high-confidence cases are automatically finalized, while uncertain or ambiguous cases are routed for clinician review. The system further incorporates a feedback adaptation processor that recalibrates model parameters and uncertainty thresholds based on expert feedback, maintaining alignment with clinical reliability standards over time. Implemented as a hardware-integrated diagnostic device, the invention supports real-time inference, secure data handling, and interpretability visualization through uncertainty heatmaps and attention overlays.

The invention discloses an intelligent triage dynamic priority judgment method for triage, and relates to the technical field of intelligent medical treatment, and the method comprises the steps: respectively collecting the visual sign characteristics, voice complaint information characteristics and voice vital sign characteristics of a patient based on a machine vision module and a voice interaction module; performing fusion analysis on the multi-modal data through a deep learning model to generate a patient injury condition feature vector; then, in combination with the real-time resource occupation condition of the medical institution, the priority scores of the patients are dynamically adjusted, the final triage level is generated, and the patient list sequence is updated in real time; according to the method, the triage efficiency can be effectively improved, the waste of medical resources is reduced, particularly in an emergency resource allocation mode, priority allocation is further optimized through the resource efficiency coefficient, and it is ensured that the most needed patient is treated preferentially when resources are insufficient.

The invention discloses a psychiatry pre-diagnosis triage knowledge reasoning method based on a knowledge graph. The method comprises the steps that 1, pre-diagnosis original data are collected and preprocessed; 2, constructing a pre-diagnosis knowledge graph of the psychiatry department; 3, obtaining a standardized chief complaint text, and carrying out semantic coding through an improved Biofer model to generate a chief complaint semantic vector; 4, performing semantic matching on the chief complaint semantic vector and a pre-diagnosis knowledge graph of the psychiatry department, and screening and reasoning an initial node set; 5, executing rule path reasoning on the pre-diagnosis knowledge graph of the psychiatry department by adopting an improved AnyBURL algorithm; step 6, constructing a recommended triage suggestion set; 7, pushing the recommended triage suggestion set to a doctor terminal interface, and generating a triage result set; and step 8, acquiring feedback information after diagnosis, and performing incremental updating on the pre-diagnosis knowledge graph of the psychiatry department and the improved Bioformer model. According to the method, the semantic understanding ability and the reasoning decision level of the pre-diagnosis triage of the psychiatry department are improved.

The invention relates to the technical field of medical treatment, in particular to a pre-hospital and in-hospital first-aid time axis dynamic tracking and analysis method, which comprises the following steps of: acquiring patient vital sign data and a chief complaint voice stream transmitted by a pre-hospital first-aid terminal in real time, inputting a special voice recognition engine, and converting to generate structured text data; extracting a patient identity label and an illness state characteristic field and writing into a time axis database; and in-hospital medical equipment operation interface signals, geo-fence trigger events and triage system events are captured in real time, and diagnosis and treatment node data with timestamps are generated and added to the time axis database. According to the method, historical node sequences in a time axis database are extracted to construct a disease feature vector set, incremental training samples are obtained after feature sorting, the progress deviation value of real-time node data is combined to match historical similar case time axis fragments to execute weighted deduction, and a prediction time sequence of a key link is generated. And a reliable basis can be provided for medical personnel to plan resource scheduling of equipment, personnel and the like in advance.

In some aspects, a triage artificial intelligence receives a portion of a conversation between a doctor and a patient, determines, based on the conversation, one or more symptoms associated with the patient, determines that the conversation includes a set of trigger words associated with a particular symptom of the one or more symptoms, selects based on the set of trigger words associated with the particular symptom, a first artificial intelligence specialist in a first medical specialty from a plurality of artificial intelligence specialists, and provides the first artificial intelligence specialist with access to the conversation between the doctor and the patient. The first artificial intelligence specialist provides one or more decision support insights that are sent to a computing device associated with the doctor.

The invention discloses an automatic triage and accurate diagnosis method fusing multi-modal medical data, and relates to the technical field of automatic triage, and the method comprises multi-modal medical data acquisition, preprocessing and representation vector construction, and realizes department recommendation, priority determination and disease probability analysis through a triage decision network and a diagnosis inference engine. Generating an interpretable path; according to the method, multi-modal data such as texts, numerical values, images, time sequences and voices are fused, technologies such as a cross-modal attention fusion network and a medical knowledge graph are adopted, accurate triage and diagnosis are achieved, meanwhile, a structured report is generated through a confidence degree evaluation and grading processing flow, data feedback and model updating are supported, image-text report reminding is provided for a patient, and the accuracy of triage and diagnosis is improved. The medical efficiency and the diagnosis accuracy are improved.

The present disclosure relates to a multidimensional adaptive sensing system and method for event detection with improved accuracy. The system dynamically adjusts, using baseline and compound models, a triggering conditional threshold of each event based on real-time variations in environmental parameters and sensor health. The adaptive system allows for fine-tuning of sensitivity to environmental changes, seasonal variations, and sensor decay, thereby reducing false positives and negatives. Installation flexibility is achieved by selecting and deploying a subset of models tailored to available data at the sensor's location, ensuring optimal operation regardless of specific environmental conditions or sensor configurations. The adaptive sensing system is used in environmental control systems for dynamic routine management, sensor health management, a triage system for complex event analysis, and multifaceted compliance assurance solution. Further, the adaptive sensing system is used for automated configuration, model deployment, and maintenance by leveraging edge computing units and a central control unit.

A method and non-transitory computer-readable medium for automating eFAST analysis of ultrasound scans. The method includes receiving at least one ultrasound image from one or more scan sites; processing the ultrasound image to determine whether there is a presence of one or more fluid pockets or free fluid present in the patient, the injury is selected from pneumothorax, hemothorax, and abdominal hemorrhage; and outputting a result from the processing. A model is trained on historical ultrasound images over a historical observation period, the historical ultrasound images associated with at least one injury determined directly observed presence of a fluid pocket or free fluid present in those images.

A method and system for detecting possible disease and condition indications on a patient, using combinations of two dimensional, infrared, and three-dimensional (such as dot) cameras. In one embodiment, the cameras are located in a smartphone that the patient uses to aim at parts of the body, wherein features or motion potentially corresponding to indications of disease or conditions are extracted and analyzed. A further embodiment conducts triage for conditions detected or otherwise. Further embodiments use augmented reality overlays to assist the patient through the various procedures, guide in the data collection, and identify to the patient necessary and useful information.

The invention discloses an emergency intelligent triage method and system based on sensing equipment, and belongs to the technical field of medical triage, and the method specifically comprises the steps: collecting vital sign data through a physiological sensing device, and constructing an initial symptom vector; retrieving disease hypotheses based on the medical knowledge graph and constructing a time sequence path tree for each hypothesis; calculating a priority score of the detection node according to the resource occupancy state and the disease association quantity; selecting an optimal first-step detection point to execute detection, and correcting the assumed confidence of each disease by adopting a confidence inversion principle based on a detection result; the process is executed through iteration, a diagnosis path is dynamically adjusted, triage is completed when the confidence coefficient of the disease hypothesis reaches a definite diagnosis threshold value, and a differential diagnosis list is output and manual triage is started when the maximum number of iterations is reached. According to the method, through resource-aware detection node optimization and confidence inversion closed-loop optimization, dynamic path planning and intelligent decision making in the emergency triage process are realized, and the triage efficiency and accuracy are effectively improved.

The invention relates to the technical field of computers, and particularly discloses a digital human intelligent hospital guide interaction system and method based on a large model, and the method comprises the steps: judging whether a patient has hesitation in a hospital guide key link or not through the residence time, verifying the demand urgency through the combination of facial expressions, and finally locking the specific department inquiry direction through disease voice. The conversion from passive response to active identification of the potential demand is realized, the identification precision of the potential department inquiry demand of the patient is improved, the potential department inquiry demand of the patient is accurately identified, and fuzzy identification of the digital human hospital guide demand is prevented; medical entity data are extracted and accurately matched with the dynamic department information base, so that the patient does not need to autonomously screen departments, the hospital guide communication cost of the patient is reduced, and low hospital guide efficiency caused by the fact that the patient does not know the departments due to diseases is avoided; and in combination with the real-time state of the department, the generated optimal moving path can adapt to the real-time position of the department and the regional people flow state, so that the dynamic adaptability and practicability of the hospital guide service are improved.

The invention relates to the field of triage in the pneumology department, and particularly provides a primary triage system for the pneumology department, and the system comprises a physical sign obtaining unit which is used for obtaining the body temperature and the disease performance of a registered patient, and the disease performance is the abnormal performance of the patient due to the disease in the recent period; the initial medical record generation unit is used for generating an initial medical record, the initial medical record generation unit obtains basic information of a patient by obtaining registration information of the patient, obtains a patient chief complaint and a current medical history through the physical sign obtaining unit, and pushes the initial medical record of the corresponding patient to a corresponding doctor when the doctor calls a number; according to the primary diagnosis triage system for the pneumology department, the disease performance of the patient is obtained in advance, and the initial medical record is generated, so that the early-stage communication time can be greatly saved during treatment, and the treatment efficiency is improved.

The invention relates to the technical field of medicine, in particular to an ophthalmology clinic system and method simulating a three-level diagnosis and treatment mode and medical device.The system comprises a triage module provided with a first diagnosis model and capable of achieving eye disease screening and early triage based on single-mode image data and clinical data of eyes of a user; the diagnosis module is provided with a data fusion model and a second diagnosis module and can realize accurate recognition and disease progress prediction of complex eye diseases, the decision module is provided with a third diagnosis model and can provide personalized eye disease treatment scheme suggestions for patients, and the patients are propagandized and educated in combination with a large language model, so that the diagnosis efficiency is improved. And the clinical decision-making efficiency and the self-management ability of the patient are improved. Therefore, the problems of limited screening capability, low accuracy, incapability of effectively predicting the development trend of diseases and the like due to the fact that ophthalmology diagnosis mostly depends on single image analysis in related technologies are solved.

The present invention is directed to a monitoring apparatus and method for preventing pressure injuries. More specifically, an apparatus and method that is portable, multi-functional, and easy to use, capable of passive monitoring, AI triage monitoring, and EMR integration that can detect deep tissue injuries, falls, and / or bed wetness, using an equitable approach to detection.

A method, device, storage medium, and electronic device for intelligent triage are disclosed, relating to the field of artificial intelligence technology. The method includes: acquiring the medical condition information of a target patient and obtaining a target patient vector based on the medical condition information (S310); vectorizing each doctor in a doctor knowledge graph to obtain multiple doctor vectors (S320); calculating the matching degree between the target patient vector and the multiple doctor vectors using a matching degree calculation model, and recommending a doctor to the target patient based on the magnitude of the matching degree (S330).

The invention relates to the technical field of intelligent medical information processing, and discloses an intelligent voice interaction robot based on natural language processing, which comprises a robot body and an interaction system mounted on the robot body, the interaction system comprises a voice receiving module, an optimization recognition module, a semantic analysis module, an intention recognition module, a task execution module and a content output module. According to the method, the robustness in a complex medical environment and a special user group is improved through a noise suppression and self-adaptive interaction strategy; through deep semantic analysis and a multi-task risk identification model, precise judgment and context perception of medical intentions and risk levels thereof are realized; and through task execution based on risk grading and multiple compliance check, high unification of intelligence and differentiation of medical service content generation and medical safety is ensured, so that efficient and reliable technical support is provided for medical fields such as medical consultation, pre-inquiry and triage processes.

The application discloses a disease pre-examination triage auxiliary method and system, relates to the technical field of disease pre-examination triage, collects patient treatment data to generate a data group, extracts features of the data group to obtain a disease feature vector, constructs a dynamic routing layer to convert the disease feature vector into a plastic weight matrix, constructs a processing cluster layer including a quick response cluster and a deep analysis cluster, inputs the plastic weight matrix into the processing cluster layer to obtain an analysis result, and outputs a treatment guide report by fusing analysis results of multiple clusters through a decision fusion layer.

The utility model relates to a hospital triage data processing device which is characterized in that transmission frames are fixedly installed at the two ends of the outer side of a storage frame, a transmission mechanism is arranged in each transmission frame, a limiting sliding plate is slidably installed on the side, away from a machine body, in the storage frame, and the transmission mechanisms are in transmission connection with the outer side of the limiting sliding plate; a transmission mechanism is arranged on the outer side of the machine body, an inserting mechanism is arranged on the outer side of the transmission mechanism, connecting plates are fixedly installed on the two sides of the outer portion of the machine body, and the inserting mechanism is connected with the interiors of the connecting plates in a sliding mode. The storage frame is prevented from rotating and protruding at will on the front side of the machine body to affect the moving portability of the whole mechanism, meanwhile, the stability of storage and placement of the keyboard in the storage frame is improved, and then direct use after the machine body and the keyboard for input are moved is facilitated. Therefore, the triage guiding efficiency of an operator using the body to the illness state of the patient and the diagnosis and treatment membership department of the patient is improved.

The invention discloses a non-contact breathing state monitoring method based on a millimeter wave radar, and belongs to the technical field of non-contact human body vital sign monitoring. The method comprises the steps that radar echo signals of a human body target are collected through a millimeter wave radar, a phase sequence is obtained through frequency mixing, filtering and phase demodulation, and breathing signals are extracted through phase unwrapping and displacement conversion; fourier transform is carried out on the respiratory signals, and the respiratory frequency and amplitude are calculated; a plurality of slope extraction algorithms are adopted, derivation is conducted on the respiration signals in the inspiration and expiration stages, and the respiration slope is obtained; and finally, integrating the respiratory rate, the amplitude and the slope, setting a threshold value and a scoring system, and quickly and accurately evaluating the respiratory distress degree. The method does not need to contact a human body, can penetrate through clothes, is suitable for various scenes such as clinical monitoring and emergency triage, and has the advantages of being easy and convenient to operate, high in real-time performance and high in reliability.

The application discloses a pediatric emergency department hierarchical treatment guidance method based on symptom analysis and an electronic device, which comprises the following steps: acquiring age information of a target patient and detecting interaction data, wherein the interaction data comprises chief complaints and accompanying symptoms; based on the age information, a hierarchical evaluation rule library matched with the age information is called, and the interaction data is calculated by level through a preset logical judgment path in the hierarchical evaluation rule library, and a target pre-examination hierarchical result is output; the target pre-examination hierarchical result and the interaction data are combined, a preset pediatric clinical diagnosis and treatment mapping rule library is called for joint matching, a target examination item corresponding to the target pre-examination hierarchical result and the symptom characteristics is screened out, and a to-be-executed examination list is generated. In this way, the pre-examination hierarchical classification can be quickly and accurately performed, and the children and their families can be guided to efficiently complete the subsequent examination and treatment.

The embodiment of the invention provides a triage auxiliary decision-making method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining multi-modal data of a target patient; wherein the multi-modal data comprises original audio data and original text data; respectively processing the original audio data and the original text data to generate a cross-modal fusion feature vector; obtaining an initial triage suggestion based on the cross-modal fusion feature vector; performing multi-level interpretable reasoning on the initial triage suggestion to generate a triage decision result; wherein the multi-stage interpretable reasoning is used for performing multi-stage verification on the initial triage suggestion, so as to generate an interpretable triage decision with a confidence interval. Through the method provided by the embodiment of the invention, the defect of incomplete information caused by dependence on a single data source in the prior art is overcome, the clinical credibility of a triage conclusion is remarkably enhanced, and the accuracy and reliability of emergency triage are improved.

The utility model provides first-aid loading equipment for multiple wounded persons, which comprises a moving mechanism, a first-aid cabin, a first-aid loading device and a second-aid loading device, the loading and unloading mechanism comprises a lifting assembly and a connection assembly, and the lifting assembly comprises a lead screw; the connection assembly comprises a supporting frame and a loading platform, the supporting frame is slidably connected to the lead screw, and the loading platform is slidably connected to the supporting frame; the stretcher supporting mechanism comprises supporting rods, and the multiple supporting rods are connected to the side wall of the first-aid cabin and arranged in the height direction of the first-aid cabin. Through the lifting assembly and the connection assembly in the loading and unloading mechanism, the problem that the moving efficiency of the wounded is affected due to the fact that a chassis of transport tools such as off-road vehicles is too high is solved. The stretcher supporting mechanism makes full use of the internal space of the first-aid cabin, and therefore multiple prone wounded persons can be transported at the same time. Compared with conventional first-aid transportation equipment at the present stage, the movable first-aid transportation equipment has the remarkable advantages of being convenient to operate, high in transfer efficiency, controllable in moving process, high in space utilization rate, capable of reducing moving pain of the wounded and the like.

A dental triage and clinical risk assessment system (100), the system (100) comprising: a first user device (102) configured to receive patient-related dental information for remote dental assessment; a first user interface (104) within the first user device (102) that is configured to guide the patient's interaction by presenting structured symptom questionnaires, image acquisition instructions, and status notifications; a communication network (110) that is connected to the first user device (102) and configured to securely transmit patient-related dental information and control signals; a processing unit (112) connected to the first user device (102) via the communication network (110) and configured to perform automated dental triage and clinical risk assessment through coordinated data analysis decision logic and routing operations, wherein the processing unit (112) comprises: a data acquisition module (114) configured to receive patient-related dental information from the first user device (102); a data preprocessing module (116) configured to validate, normalize and structure the received dental information for analytical processing; a triage intelligence module (124) configured to analyze the structured dental information to generate a quantified urgency score and risk classification level using combined analytical logic; a decision support module (130) configured to assign the urgency score and risk classification level to a recommended dental care pathway; a nursing navigation module (134) configured to generate routing instructions corresponding to emergency referrals, scheduled consultations, teleconsultations or automated guidance; a learning and analysis module (144) configured to update internal analytical parameters based on confirmed clinical results; a storage unit (154) connected to the processing unit (112) and configured to store patient data, analytical results, priority points, routing decisions and result feedback for continuous system operation; a second user device (158), connected to the processing unit (112) via the communication network (110) and configured to receive triage outputs and recommendations for care pathways; and a second user interface (160) in the second user device (158), configured to display risk indicators, urgency points, patient data summaries and override controls for interaction with the clinician.