2030 results about "Medical systems" patented technology

The invention discloses a data analysis platform management method and system, and belongs to the technical field of computer data processing, and the method comprises the steps: obtaining multi-source heterogeneous data from a medical information system; establishing a cross-system data association model, performing dynamic feature extraction and weight distribution on multi-source heterogeneous data, and outputting a resource supply-demand relationship graph; analyzing the resource supply-demand relation graph, and identifying business conflicts in medical resource scheduling; generating a conflict solution of the business conflict based on a multi-objective optimization algorithm, and generating an execution instruction; and issuing an execution instruction to the target medical system, verifying an execution result of the execution instruction, and updating system parameters. According to the method, a cross-system dynamic modeling and multi-objective optimization strategy is adopted, and a closed-loop verification mechanism and a multi-source heterogeneous data fusion technology are combined, so that intelligent prediction, accurate scheduling and self-learning optimization of medical resource conflicts can be realized, full-process traceable execution of high-value consumables is ensured, and the resource utilization efficiency and the emergency response capability are comprehensively improved.

The invention discloses an ophthalmologic operation real-time navigation system and method based on dynamic visual field tracking, and relates to the technical field of medical systems. Comprising the following steps: matching operation data closest to a current operation from a database, and generating standard operation navigation of the current operation; the real-time image of the operation process is compared with the image of the standard operation navigation in real time, the step of the current operation is determined, and meanwhile subsequent image navigation of the operation of the patient is displayed; generating a spatial mapping matrix between an eyeball movement track and a target region by combining target region boundary data of preoperative OCT image segmentation and an intra-operative navigation coordinate system; the virtual navigation path of the surgical instrument is dynamically corrected according to the real-time eyeball movement track, so that the surgical instrument is aligned with the target area, the spatial relation between the instrument and the target area can be visually mastered through the overlapping display of the three-dimensional virtual path and the real-time image, unconscious displacement or physiological tremor of a patient in an operation is actively adapted, and the operation accuracy is improved. And the continuous accuracy of the navigation path is ensured.

The invention discloses an osteoarticular disease rehabilitation training optimization system, and relates to the field of medical training, and the system comprises an authority control module which is used for connecting an electronic medical system, obtaining the reading authority of historical and current medical data of a patient, and obtaining the instruction control and data reading authority of each functional module; the multimode acquisition module is used for acquiring pathological bone joints, associated musculoskeletal data and personal basic data through the authority control module, and converting original data into feature vectors of muscle activation degree, bone joint activity degree and skeleton stress distribution of a corresponding area of a patient body; by integrating medical data, musculoskeletal features and economic condition information of a patient, a personalized model is constructed to output an optimal adaptive training item and specific data thereof, the compensatory load of a non-ill-conditioned joint is evaluated, and timely intervention is performed through a fusing mechanism when abnormity is monitored in real time, so that the safety is ensured.

In one embodiment, a medical system includes a catheter configured to be inserted into a chamber of a heart of a living subject, and including multiple electrodes configured to capture electrical activity from electrical activation signals propagating in tissue of the chamber, a display, and processing circuitry configured to automatically select bipolar signals to be captured into an electro-anatomical map from respective electrode pairs of the multiple electrodes responsively to an alignment of the respective electrode pairs with a direction of propagation of the electrical activation signals, and render the electro-anatomical map to the display.

The invention relates to the technical field of medical systems, and particularly discloses an anesthesia complication prediction model construction method based on deep learning, and the method comprises the following steps: S1, obtaining multi-source heterogeneous anesthesia medical data; s2, constructing a multi-modal feature fusion module; s3, designing a hierarchical deep neural network architecture which comprises sub-networks for processing different modal data in parallel and a full-connection prediction layer fusing multi-modal features; s4, continuously outputting a complication probability curve in a sliding time window mode by adopting a dynamic risk trajectory prediction mechanism instead of a single static prediction result; and S5, deploying a clinical real-time decision interface, and mapping a prediction result to an anesthesia monitoring equipment alarm system in real time. A bidirectional LSTM + 1D-CNN hybrid encoder and a cross-modal attention mechanism are adopted, time sequence dependence of physiological signals and spatio-temporal characteristics of operation events are synchronously captured, deep semantic fusion of multi-source data is achieved, and the characterization capacity of a model for precursor characteristics of complications is improved.

A fluid management system for use in a tissue resection procedure includes a controller. An inflow pump is operated by the controller and configured to provide fluid inflow through a flow path to a site in patient's body. An outflow pump is operated by the controller and configured to provide fluid outflow through a flow path from the site in patient's body. A motor driven resecting device may be provided for resecting tissue at the site. The controller is configured to actuate an inflow pump and an outflow pump in response to various signals and various algorithms are provided to provide malfunction warnings and assure safe operation.

Systems and methods for designing and implementing patient-specific surgical procedures and / or medical devices are disclosed. In some embodiments, a method includes receiving a patient data set of a patient. The patient data set is compared to a plurality of reference patient data sets, wherein each of the plurality of reference patient data sets is associated with a corresponding reference patient. A subset of the plurality of reference patient data sets is selected based, at least partly, on similarity to the patient data set and treatment outcome of the corresponding reference patient. Based on the selected subset, at least one surgical procedure or medical device design for treating the patient is generated.

The invention relates to the technical field of intelligent medical systems, and discloses a cerebral apoplexy onset risk assessment and reminding method and system.The method comprises the steps that continuous medical structured detection data are collected, and the data comprise carotid artery blood flow parameters, brain oxygen saturation, heart rate variability and metabolic indexes; inputting a bidirectional LSTM, a differential convolutional network, a wavelet residual network and a multi-layer perceptron to extract nonlinear features; constructing a neural function coupling structure diagram of four nodes of cerebral blood supply, oxygen supply, autonomous regulation and metabolic steady state; calculating inter-node time sequence offset correlation and a stable factor to obtain a coupling anomaly coefficient; and driving the embedded network by using a graph structure and a node feature input mechanism, and outputting a risk state assessment result. According to the method, the neural function coupling structure diagram is constructed and the mechanism is introduced to drive the embedded network, so that high-precision identification of the multi-system collaborative abnormal state and dynamic evaluation of the stroke risk level are realized.

The invention discloses a medical knowledge constrained multi-modal time series data dynamic evaluation method and a wearable medical system. According to the method, a mixed perception architecture is constructed through an improved Swin-Transform time sequence encoder and a graph neural network, a medical priori mask matrix is embedded to constrain an attention mechanism, and time sequence feature extraction and cross-parameter correlation modeling of multi-modal physiological signals are enhanced; a dynamic quality evaluation model is designed, data integrity, cross-modal consistency and diagnosis effectiveness indexes are fused, an evaluation weight is adjusted in real time in combination with an adaptive weight function, and quantitative association of data quality and clinical diagnosis confidence is achieved; and when the motion artifacts or pathological conflicts are judged to exist, starting an abnormal positioning and correcting mechanism. According to the method, noise such as motion artifacts and interference can be monitored at any time, the attention to different indexes is adjusted in real time according to the risk level, and the pathological recognition accuracy and clinical credibility are improved by fusing multi-mode perception of medical knowledge.

Disclosed herein are medical systems, pads, and methods for exchanging thermal energy between a circulating fluid and a patient. Some pads are configured multiple uses on the same patient or across multiple different patients. Some pads include multiple layers of hydrogel disposed on one or both sides a fluid compartment. Removable hydrogel layers expose other hydrogel layers for subsequent uses of the pad. Removable storage liners encapsulate one or multiple hydrogel layers. Separation liners between adjacent hydrogel layers isolate the adjacent hydrogels from each other and removal of the separation liner extends the operational life a hydrogel layer. Adhesive patches secure the pads to the patient including adhesive patches extending through openings of a pad. Some pads are configured for disinfection, sterilization and / or laundering. In an embodiment, the fluid is air and a vacuum within a compartment of the pad secures the pad to the patient.

The invention relates to the technical field of medical system management, and particularly provides an outpatient medical insurance chronic disease medical data processing system based on artificial intelligence NLP. The system comprises a knowledge graph construction component which is configured to integrate multi-source heterogeneous data such as medical records, medical insurance and signs, perform cleaning, normalization and structural processing on the data through an NLP technology, and construct a chronic disease medical data knowledge graph; the diagnosis and treatment scheme matching component is configured to perform semantic analysis on the medical insurance policy document and the diagnosis and treatment guide through an NLP technology, and match a diagnosis and treatment scheme and a medical insurance reimbursement path in combination with the actual illness state and the medical insurance reimbursement record of the patient; the analysis and early warning assembly is configured to analyze the long-term health data of the chronic disease patient, identify potential health risks and development trends, and provide personalized health management suggestions and early warning prompts. According to the method, multi-source data integration and knowledge graph construction are achieved through the NLP technology, and the problem of data heterogeneity and the semantic association requirement are solved.

The invention discloses a multidisciplinary combined diagnosis and treatment method and system, relates to the technical field of intelligent medical systems, and solves the problems that traditional manual consultation is low in efficiency and is greatly interfered by human factors, simple system recommendation is inaccurate, and diagnosis and treatment requirements of patients are difficult to meet. The method comprises the steps of generating a consultation scheme based on a preset matching degree standard, an illness condition and a diagnosis and treatment specification, triggering a payment process after system compliance verification, and locking consultation resources after payment succeeds; according to the illness state emergency degree of the patient, expert scheduling information and hospital resource occupation condition, intelligent scheduling is carried out to generate a consultation time arrangement, and meanwhile, consultation invitation and detailed information are sent to related experts; and after the consultation is finished, the system arranges text records, fuses expert opinions, generates a structured consultation report and pushes the structured consultation report to a patient end. The method has the advantages that intelligent management of multidisciplinary joint diagnosis and treatment is achieved, medical resource configuration is optimized, diagnosis and treatment efficiency and accuracy are improved, and medical experience of patients is improved.

Embodiments of the present disclosure provide a medical system and method. The medical system includes an equipment room, a plurality of medical rooms, the imaging device, and a plurality of shielding doors. The imaging device includes the movable imaging component. The movable imaging component is shared by the plurality of medical rooms, and the movable imaging component is configured to move between the equipment room and the plurality of medical rooms. For each of the plurality of shielding doors, the shielding door is provided between one of the plurality of medical rooms and the equipment room.

The invention discloses a mild cognitive impairment brain rehabilitation training device and system in the technical field of cognitive nerve rehabilitation, and the device comprises a multi-modal data fusion module, a personalized training task generation module, a multi-sensory stimulation presentation module and a real-time adaptive regulation and control module. And the personalized training task generation module is used for dynamically generating a personalized narrative training task fusing the user interest theme and the cognitive training target by utilizing a reinforcement learning algorithm based on the user cognitive weak domain evaluation result and the user personal interest and life narrative content obtained through natural language processing. Clinical data of a patient and real-time electroencephalogram and behavior data are fused, a narrative training task deeply fused with life experience and interest of the patient is dynamically generated, the difficulty of the training task is automatically adjusted according to real-time physiological indexes, meanwhile, seamless connection with a medical system is achieved through digital biomarkers, and the training efficiency is improved. And the precision and compliance of rehabilitation training are obviously improved.

The present invention discloses a method, device, storage medium, and medical system for generating a restoration dental model. Among them, the method comprises: obtaining the restoration type of the tooth to be restored, wherein the restoration type includes at least one of the following: tooth implant type, crown restoration type, and inlay restoration type; determining the key points of the tooth to be restored based on the restoration type, where the key points of the tooth to be restored are used to represent the characteristics of the tooth to be restored; determining the restoration dental model based on the restoration type and the key points of the tooth to be restored. The present invention solves the technical problem of low efficiency of making restoration dental models artificially in related technologies.

The invention relates to the technical field of medical systems, in particular to a multi-disease fusion prediction method and system, and the method comprises the steps: obtaining a medical sequence code, and outputting a disease vector; obtaining a gating memory model, obtaining a doctor-seeing time interval, and configuring an additional time gate based on the doctor-seeing time interval and the disease vector; updating the gated memory model based on a time gate to obtain a health memory state and a context disease hiding state; aggregating the context disease hiding states to obtain aggregation states, calculating attention scores corresponding to the aggregation states, and outputting patient disease states based on the attention scores and the aggregation states; demographic statistical characteristics are obtained, and integration is carried out in combination with the disease state of the patient to obtain a combined vector; and mapping the combined vector to disease risk probability distribution to obtain a prediction result. The method and the device have the effect of predicting various diseases through the general data.

A system and method are provided for aligning a tool with a targeted axis in tissue to perform a medical procedure. A medical plan is registered to the location of the tissue using a computer-assisted medical system, where the medical plan include a planned position for the targeted axis based on pre-procedure data. The tool is aligned with the planned position for the targeted axis using a computer- assisted medical system. The computer-assisted medical system includes a hand- held device having a handle and a working portion adjustable relative to the handle so as to orient the tool. A computing system is also provided comprising a tracking system and a control system for registering the medical plan to the location of the tissue, tracking the hand-held device relative to the tissue and the medical plan, and adjusting the working portion of the hand-held device relative to its handle.

A non-transitory machine-readable media may store instructions that, when run by one or more processors, cause the one or more processors to generate stereo endoscopic image data of a medical field and define a medical field volume from the stereo endoscopic image data. The processors may also project a 3D representation of the medical field volume to an extended-reality display device in a remote volume. The 3D representation may include a stereoscopic image and a 3D scene generated from the stereo endoscopic image data. The processors may also generate visual guidance in the remote volume to augment the stereo endoscopic image, map the visual guidance from the remote volume to the medical field volume to generate an augmented image of the medical field volume, and project the augmented image of the medical field volume to a display device viewed by an operator of instruments in the medical field.

The invention discloses a medical dialogue search term rewriting method and device, equipment and a storage medium. The method comprises the following steps: detecting whether current dialogue input is a question or has intention jump through a lightweight model for multi-round dialogue intention jump and question recognition; when it is detected that the current dialogue input is subjected to intention hopping or not questioning, the historical dialogue context is emptied, and the current input serves as independent query to be directly output; and when it is detected that the current dialogue input does not have intention hopping and the current dialogue input is a question, triggering the functions of substitution disambiguation and semantic completion, calling the fine-tuning and rewriting large model, and generating a standard medical question with complete semantics and standard terms, so that the context dependency relationship in the user dialogue can be accurately identified, and the user experience is improved. In addition, a large model can be called to complete deep semantic reconstruction when necessary, light model pre-judgment and large model accurate rewriting are combined, accuracy and efficiency are both considered, and the method is a key technical breakthrough for improving usability and specialty of a medical RAG system.

The invention relates to the technical field related to medical systems, in particular to a medical teaching and research integrated system based on a common bottom layer, and aims to break through information islands among medical treatment, teaching and scientific research and realize closed-loop linkage and dynamic knowledge conversion of a whole process. The system comprises a diagnosis and treatment decision subsystem, a scientific research queue management subsystem and a teaching subsystem, integrates data through a three-in-one data engine, and realizes information sharing and cooperative work. The diagnosis and treatment decision subsystem provides diagnosis and treatment support for severe diseases based on an expert thinking chain. And the scientific research queue management subsystem is responsible for screening cases, sorting data, implementing quality control and statistical analysis, and adjusting an expert thinking chain according to scientific research results. And the teaching subsystem carries out teaching by using a standardized case presentation mode. Through a feedback closed loop of clinical discovery, scientific research verification, knowledge updating and teaching feedback, rapid propagation and application of medical knowledge are promoted, and the medical service quality and the medical education level are improved.

The invention relates to a layout image generation method and device, computer equipment and a storage medium, and the method comprises the following steps: carrying out the element analysis of original image data, and obtaining image element information; performing feature extraction on the image element information to obtain image features and text features; performing hypergraph structure construction according to a preset design rule, the image features, the text features and the image element information to obtain hypergraph structure information; performing style parameter adjustment and coordinate adjustment on the hypergraph structure information according to the matching similarity corresponding to the element embedding vector to obtain to-be-rendered information; and performing image layout rendering according to the to-be-rendered information to obtain an effective layout image. The method can be applied to application scenes of financial science and technology and digital medical systems, and insurance product propaganda images or disease prevention propaganda images which effectively express image elements and features can be effectively, accurately and quickly generated according to original insurance product images or health education images in the system.

Medical systems, devices, and methods for determining whether a blood vessel is a vein or an artery. The system includes an optical fiber configured for insertion into a blood vessel coupled with a console having a light source, an optical receiver, processors, and logic stored in memory. The optical fiber includes sensors disposed along its length configured to determine a state or condition of the optical fiber. The state or condition can include a strain, movement, pressure, and / or temperature. The logic is configured to analyze reflected signals from the sensors to determine whether the optical fiber is inserted within an artery or within a vein. The logic may also determine a red-blue shift of a projected light to determine a blood flow direction with respect to the optical fiber.

The invention discloses a medical institution medical consumable access selection evaluation method and system, and relates to the technical field of medical systems. Comprising the following steps: responding to an evaluation request of a target consumable, generating an evaluation task according to an evaluation index and an evaluation object, and distributing the evaluation task to the corresponding evaluation object; the evaluation indexes comprise a clinical value, an economic value, a patient value and a management value, and performing importance scoring on each index to obtain a corresponding weight of each evaluation index; collecting scoring results of all the evaluation objects on the target consumable, and performing linear weighting on the scoring results of the evaluation indexes according to the corresponding weights to obtain an evaluation result of the target consumable; by constructing a multi-dimensional dynamic evaluation system, an intelligent data fusion mechanism and an automatic task distribution mechanism, the manual process cycle is greatly shortened, the limitation of traditional single-dimensional evaluation is broken through, a linear weighted model is utilized to fuse multi-dimensional scoring results, the scientificity and efficiency of medical consumable admission selection are improved, and the clinical application quality of consumables is improved.

The invention discloses an intelligent medical system suitable for an internet hospital, and relates to the technical field of intelligent medical treatment, and the system comprises the following steps: building an electronic health record, and obtaining the information of a patient; performing remote diagnosis and treatment according to the patient information to obtain a diagnosis and treatment result; performing medicine management according to the diagnosis and treatment result to obtain medicine management information; performing patient health monitoring according to the medicine management information to obtain patient health data; personalized health suggestions are made according to the health data of the patient, and health suggestions are obtained; performing patient health tracking and feedback according to the health suggestions to obtain health feedback; making and adjusting a rehabilitation plan according to the health feedback to obtain the rehabilitation plan; and performing health assessment and diagnosis and treatment feedback according to the rehabilitation plan. The accuracy of drug recommendation is improved, the safety and effectiveness of a treatment scheme are ensured, the scientificity and individual adaptability of health suggestions are improved, and the effectiveness and sustainability of a health management scheme are enhanced.

Systems or techniques that facilitate automated role-based access control for patient health information security and compliance are provided. In various embodiments, a system can access historical data corresponding to medical systems. In various aspects, the system can generate, based on the historical data, automated role-based access control rules. In various instances, the system can employ a trained machine learning model to detect, based on the automated RBAC rules, user access anomalies from audit logs of the medical systems. In various embodiments, the system can visually render the detected user access anomalies on a graphical user interface.

Disclosed herein is a medical system (100, 400) comprising: a magnetic resonance imaging system (102) configured for providing a respiratory signal. The respiratory signal is descriptive of a respiratory position as well as of inhalation and exhalation of the subject. The execution of machine executable instructions (140) causes the computational system to repeatedly: perform (200) the individual acquisition of k-space data using the magnetic resonance imaging system; receive (202) the respiratory signal; bin (204) the individually acquired k-space data into one of a predetermined number of k-space bins (148) using the respiratory signal and perform outlier rejection. Execution of the machine executable instructions further causes the computational system to reconstruct (208) a magnetic resonance image for each of the predetermined number of k-space bins to provide a respiratory-state resolved magnetic resonance image (150).

A BTE prosthetic device for use in a medical system or prosthesis comprises a connector configured to mechanically attach an auxiliary device of the system to the BTE prosthetic device. The connector is electrically connected to a transceiver of the BTE prosthetic device. The connector operates as an electromagnetic antenna for transmitting and / or receiving signals between the BTE prosthetic and other components of the medical system.

The invention relates to the technical field of intelligent medical systems, medical instruments, monitoring equipment and the like, and provides a medical intelligent turning-over nursing system and a medical intelligent turning-over nursing pad. An intelligent air cushion module is arranged to monitor the pressure borne by each air bag on an air cushion in real time, and then a multi-parameter vital sign monitoring module is arranged to monitor the pressure borne by each air bag on the air cushion in real time; key vital sign data of a bedridden patient are collected in real time, then an air cushion host is arranged, and the inflation and deflation states of the corresponding air bags are controlled according to individual feature data and the key vital sign data of the bedridden patient and pressure data borne by different air bags so as to adjust the body stress of the bedridden patient on the air cushion. Therefore, the body stress condition and the vital signs of the patient are monitored in real time, a more comprehensive and personalized nursing strategy is provided in combination with the individual characteristics of different patients, and the nursing accuracy is improved.

The invention belongs to the technical field of complication prevention, and particularly relates to a rehabilitation equipment integrated management and data interaction system based on a mobile terminal, which comprises a multi-source data acquisition module, a data integration and preprocessing module, an intelligent analysis module and a risk early warning module, data islands are cracked through a multi-source heterogeneous data fusion architecture, and an extensible access layer is designed; the system is compatible with medical systems such as HIS, LIS and PACS; a Bluetooth module, a Wi-Fi module and a 5G module are embedded and directly connected with rehabilitation equipment such as a power bicycle and an inspiratory muscle training instrument; cross-institution data collaboration is realized through a federated learning framework, for example, local training sub-models of hospitals and global parameter aggregation of a central server are realized, model generalization is improved on the premise of privacy protection, 'preoperative, intra-operative and post-operative link splitting 'is broken, and a perioperative period full-link data set is constructed.

The invention discloses an intelligent monitoring and regulation system for a power transformer, and relates to the technical field of intelligent monitoring and regulation of power transformers. Comprising an initial automatic regulation module, a data acquisition and transmission module, a data preprocessing and feature extraction module, a feature analysis and prediction module, a load classification module, a conventional load regulation and control module and a high-frequency load adaptive regulation and control module. Load data are collected in real time through the Internet of Things, the load change type is predicted through machine learning, and for a conventional load, the initial frequency is kept to reduce abrasion; for a high-frequency load, the frequency of the tap switch is adaptively increased, rapid response of the transformer is ensured, and equipment faults caused by unstable voltage are avoided, so that efficient operation of the transformer is ensured in different load scenes, the overvoltage or undervoltage risk is reduced, reliable power supply is provided for industrial equipment and a medical system, and the stability and safety of a power grid are improved.