132 results about "Clinical work" patented technology

According to the modularized ultrasonic-guided lumbar puncture teaching model provided by the invention, on the basis of the detachable modularized ultrasonic-guided lumbar puncture teaching model, the pathological bony structure module for simulating the corresponding pathological conditions of the lumbar structure is introduced, so that the lumbar puncture process in different pathological states is simulated; therefore, trained medical staff can be helped to better understand the anatomical basis and operation key points of lumbar puncture, the understanding of different pathological changes is deepened, and an experimental platform is provided for studying the improvement of lumbar puncture operation, the occurrence mechanism of puncture-related complications and the like. Furthermore, better lumbar puncture operation in actual clinical work is promoted through a better teaching and training effect, and the medical service experience and personal safety of a patient are guaranteed.

The invention discloses a chest radiograph report generation and focus positioning method and system based on reinforcement learning, and belongs to the technical field of artificial intelligence and medical image analysis crossing. According to the method, firstly, a basic model is supervised and fine-tuned by using a multi-source chest radiograph image and a query text; and then optimizing the strategy model by adopting a GRPO reinforcement learning framework, introducing an indicator function guided by token entropy into a target function, and finally realizing parallel generation of an end-to-end chest radiograph report text and focus bounding box coordinates by the optimized strategy model. According to the method, visual positioning of the focus is realized while the generation quality of the chest radiograph report is improved, and the integrated output form of the method better fits the clinical actual working process.

The utility model relates to the technical field of arterial sheathing canals, in particular to a femoral artery sheathing canal with a fixing patch, which solves the technical problems that two persons cooperatively control the femoral artery sheathing canal in the prior art, time and labor are wasted, and the operation time is prolonged, and comprises a sheathing canal body, a hemostasis sheathing canal seat, a three-way valve and a flexible fixing patch, the middle of the flexible fixing patch is fixedly connected with a hard special-shaped clamping groove, and the hard special-shaped clamping groove is matched with the hemostasis sheath tube base, the end of the sheath tube body connected with the hemostasis sheath tube base and the end of the connecting tube. A notch is formed in the flexible fixing patch, and after the hemostasis sheath tube base is clamped and matched with the hard special-shaped clamping groove, the end of the hemostasis sheath tube base corresponds to the notch in position; the lower surface of the flexible fixing patch is provided with a bonding layer used for being pasted on the skin. The femoral artery sheath tube can ensure that necessary passages of a femoral artery approach nerve interventional operation are smooth, manpower resource waste in clinical work is reduced, the probability that the femoral artery sheath tube is disengaged is greatly reduced, and it is ensured that the nerve interventional operation is carried out safely and smoothly.

A method, computer program product, and computing system for generating an internal state prompt with medical content and a multi-action task to perform on a healthcare system. A first output healthcare system command is generated by processing the internal state prompt using a trained multimodal generative artificial intelligence (AI) model. The first output healthcare system command is converted into a first healthcare system-executable command associated with the multi-action task for a first target healthcare subsystem. Modified medical content is generated by executing the first healthcare system-executable command on the medical content using the first target healthcare subsystem. The internal state prompt is updated with the modified medical content generated by executing the first healthcare system-executable command and the first output healthcare system command listed as a past action performed during execution of the multi-action task.

A method for cardiac diagnostic analysis is provided. The system includes a processor and memory coupled to the processing unit, receiving data from standard 12-lead ECGs from an external device; at least one computer-readable storage medium containing instructions, including program code that causes the execution of procedures according to the programs encoded on a disk or other media capable of using advanced algorithms such as deep learning networks, so that they can be processed during any given procedure without substantially altering the existing clinical workflow.

A clinical workflow optimization system includes a data processing and analysis platform electrically connected or communicatively coupled to a user device and an HIS server, and a generative AI model set communicatively coupled to the data processing and analysis platform. The data processing and analysis platform provides one or more assistant tools. When the user device selects an assistant tool to execute a task instruction, the data processing and analysis platform uses one model of the generative AI model set to interpret and execute the task instruction. The analysis platform presents the execution result of the task instruction to the user device, wherein data required to execute the task instructions is recorded in the content of the task instructions or provided by the HIS server, the user device, or an external database. On the platform, users can independently develop and build clinical data processing tools using natural language.

The invention belongs to the technical field of osteoarthritis management, and particularly relates to an osteoarthritis management system based on artificial intelligence and a computer storage medium. The invention provides an osteoarthritis management system based on artificial intelligence. The system integrates an LLM-DL hybrid architecture, a multi-specialist module cooperation framework and an RAG knowledge base system, and can cover a complete clinical process from patient preliminary diagnosis to treatment scheme formulation. The system can comprehensively and accurately evaluate the disease state of a patient, provides personalized disease progress prediction, not only predicts 2-year and 4-year functional results and iconography progress, but also can identify specific risk factors of the patient, and provides a basis for accurate intervention. Through the design of the whole system, the clinical working efficiency and the prediction accuracy are remarkably improved, the dependence on specialist doctors and high-end equipment is reduced, high-quality KOA management can also be implemented in resource limited areas, and therefore the overall medical resource requirement is effectively reduced.

The invention discloses a genetic disease pathogenic site sorting and diagnosis auxiliary method and system based on multi-modal artificial intelligence. The method comprises the following steps: firstly, collecting genetic disease data to construct a heterogeneous knowledge graph; the method comprises the following steps: acquiring patient data, and executing an analysis process: generating multi-modal feature representation of candidate pathogenic sites from four dimensions of variation features based on rules, a tissue specificity mechanism, a protein three-dimensional structure and real-time literature evidence; carrying out fusion sorting on the features by using a sorting model, and generating an interpretable report and a clinical examination suggestion based on the uncertainty of a sorting result; and after the doctor executes examination according to the suggestion and feeds back newly added data, the analysis process is repeated until a preset iteration target is achieved. According to the method, the limitation of a static analysis model is broken through, multi-dimensional evidence fusion and clinical workflow embedding are realized, and the interpretation accuracy and diagnosis efficiency of the pathogenic site of the genetic disease are remarkably improved.

The invention discloses an olfactory function detection kit and an olfactory scoring method, and the olfactory function detection kit is characterized in that six flavors of garlic, bromhidrosis, vinegar, lemon, fennel and mint are prepared into solid olfactory elements, and the solid olfactory elements are small in volatility, easy to store, strong in durability and simple to prepare. On the basis of clinical research on normal people and people with abnormal olfaction, a set of adaptive calculation formula is integrated, operation and calculation are more convenient, specificity and sensitivity are both improved, and compared with a conventional olfaction detection method, clinical working efficiency is improved, preparation is more convenient, storage is convenient, cost is low, and the method is more suitable for evaluation of olfaction functions of Chinese people. The detection kit provided by the invention has good detection performance and clinical applicability, and can effectively improve the detection accuracy.

Disclosed herein are methods for selecting and preparing patient data to facilitate the adoption and customized training of machine-learning models in clinical settings, particularly for radiation therapy treatment planning. The disclosed embodiments streamline the customized training process through an automated workflow that includes prefiltering patient metadata, retrieving relevant DICOM files, optional data anonymization, and generation of training data. The data is then organized into a format suitable for machine-learning training. The embodiments discussed herein reduce manual labor, minimize errors, and accelerate the integration of machine-learning into clinical workflows, enabling clinics to train and implement predictive models that replicate specific clinical practices, thereby enhancing treatment precision and improving patient outcomes.

A robotic surgical simulation system for clinical workplace simulation includes a virtual reality headset configured to display the clinical workplace simulation, a processor, and a memory. The memory includes instructions stored thereon, which, when executed by the processor, cause the robotic surgical simulation system to: generate a virtual operating room within a three-dimensional coordinate space. The virtual operating room includes a virtual surgical console. The instructions when executed by the processor further cause the system to compute, based on the captured image, a position of the user within the three-dimensional coordinate space relative to the virtual surgical console; and determine whether a user is engaged with or disengaged from the virtual surgical console based on the computed position.

A method for controlling user interfacing with a patient information system. The method includes tracking (12), by means of a position tracking system (40), a position of at least one clinical staff member (82); detecting (14) a trigger event; obtaining (16) information from a patient information system (50) in response to the trigger event, wherein the patient information system is configured to provide access to information related to a plurality of patients; identifying (18) one or more output devices (62_n) from a plurality of output devices (62_1,...,62_N) based on a detected position of the at least one clinical staff member (82), wherein each of the plurality of output devices is operable to output clinical information to a user; and causing (20) the obtained information to be communicated to the identified one or more output devices.

The utility model relates to the technical field of medical instruments, and provides a sphygmomanometer cuff and a sphygmomanometer, the sphygmomanometer cuff comprises: a body used for surrounding the arm of a subject; a lining is arranged on at least part of the inner side face of the body, and grids used for generating friction with light and thin clothes on the arms of a subject are arranged on the lining. According to the sphygmomanometer cuff, the lining is arranged on at least part of the inner side face of the body, the grids used for generating friction with light and thin clothes on the arm of a subject are arranged on the lining, and due to the arrangement, displacement of the cuff can be reduced, falling can be prevented, clinical workload can be reduced, and the accuracy of a monitoring result can be improved.

The invention relates to the technical field of medical equipment and image guidance, and discloses a high-precision image guidance treatment supporting system, method and device, and the system comprises an image guidance module, a space distance measurement module, an artificial intelligence processing module, a closed-loop feedback control module, and a motor driving module. The method comprises the following steps: collecting coordinates of a tumor area and a treatment bed deformation model, combining real-time pose information, utilizing artificial intelligence to generate a pose compensation parameter, outputting a six-degree-of-freedom compensation control instruction, and driving a motor to realize accurate adjustment of the position and the pose of the treatment bed. Real-time accurate adjustment of the treatment bed under six degrees of freedom can be achieved, multi-source data fusion and an artificial intelligence compensation mechanism are combined, the positioning accuracy and the alignment stability of a tumor area are effectively improved, position errors caused by manual operation or deformation of the treatment bed are reduced, and the accuracy of the treatment bed is improved. And the safety, the accuracy and the clinical working efficiency of radiotherapy are remarkably improved.

This invention relates to the field of medical data processing technology, and discloses a method, system, device, and medium for calculating the synergistic control rate of drug infusion. The invention acquires the patient's real-time bispectral index (BSE) and determines its deviation from a preset target range. A control algorithm is then used to calculate the required total effect intensity adjustment. Based on a preset fixed ratio of propofol and remifentanil effect-site concentrations, the total effect intensity adjustment is allocated to the target effect-site concentrations of each drug. Finally, the target infusion rates of propofol and remifentanil are calculated backward using the Schnider and Minto models, respectively. This invention achieves synergistic closed-loop control of sedative and analgesic drugs based on a single BIS feedback, solving the clinical problem of unquantifiable analgesia control, ensuring a dynamic balance between sedation and analgesia, and incorporating a built-in safety verification mechanism. This significantly improves the accuracy, stability, and safety of anesthesia depth control, while reducing clinical workload.

Systems and methods for agentic clinical workflow governance with deterministic human escalation boundaries are disclosed. A hardware-isolated governance engine enforces consensus, risk, and regulatory constraints across multi-agent clinical workflows, deterministically freezing execution and escalating control to verified human oversight when required.

The invention discloses an ultrasonic report generation method, related equipment and a computer program product, and relates to the technical field of artificial intelligence. According to the method, streaming recognition is performed on the real-time spoken voice of the doctor in the ultrasonic detection process of the doctor, the current voice transcription text fragment is obtained, the large model is called to extract the ultrasonic detection parameters in the current voice transcription text fragment in a fast thinking mode, and the extracted ultrasonic detection parameters are output and previewed in real time, so that the accuracy of ultrasonic detection is improved. Therefore, real-time interaction with doctors is generated, and the result of the detection process is transparent to the doctors. After ultrasonic detection is finished, a large model is called to generate ultrasonic description and diagnosis based on an original complete voice transfer text in a slow thinking mode, ultrasonic detection parameters, the ultrasonic description and diagnosis are integrated to obtain a high-quality ultrasonic report, the clinical requirement of real-time interaction is met, the clinical working efficiency is improved, and the clinical experience is improved. And the quality of the finally obtained ultrasonic report can be ensured.

The present application relates to the medical care form technical field, propose a kind of medical care intelligent form generation method and system based on multimodal big model, comprising: collecting the physical examination of clinical business system in medical care patient, diagnosis record, diagnosis voice data and other multimodal data;Again, generate physical change sequence by multimodal big model in combination with physical examination data, construct diagnosis feature vector;Subsequently, the vector is mapped to medical quality index system, to generate visual form framework;Then, extract diagnosis record key elements and fill into framework, update form information in combination with diagnosis voice data;Finally, medical care intelligent form adapted to each system is output by multimodal big model, and is synchronized to medical care work terminal.The present application realizes the effective fusion of multimodal medical data, and the generated form can completely reflect the whole picture of diagnosis and treatment and the dynamic evolution of signs, improve the clinical work efficiency and medical quality.

The invention discloses a multi-dimensional physiological signal monitoring system for mental stress of nursing personnel. The system comprises a signal acquisition module, a context acquisition module, a processing analysis module and an output module. The signal acquisition module is used for acquiring multi-dimensional physiological data such as an electrocardiosignal, a motion signal and an environment signal of a nurse in real time; the context acquisition module acquires a clinical operation log from a hospital information system; the processing analysis module is used for distinguishing psychological pressure from physiological interference through a multi-modal signal fusion filtering technology, intelligently associating an effective pressure event with clinical operation and determining the context of a pressure source; and the output module is used for generating a personalized pressure analysis report and a management instrument panel containing the clinical work context. The problems that in the prior art, pressure monitoring specificity is poor, and a pressure source is unknown are solved, accurate monitoring and intelligent source tracing of the psychological pressure of nursing personnel in a real clinical environment are achieved, and a scientific basis is provided for individual pressure management and organization health intervention.

A healthcare system accommodates spasmodic clinical workflows for populating a records database associated with a surgical platform or other digital healthcare platform. An interoperability engine receives data streams including events from various electronic health records systems that provide data events according to varying format, order, and timing dependent on their corresponding clinical workflows. The interoperability engine maps indeterminate events to expected events associated with a clinical workflow based on a clinical workflow management file, an industry standard model, a general parsing model, or a combination thereof. The interoperability engine may furthermore detect non-compliance of received events and may generate feedback indicative of a compliance assessment.

The invention discloses an injector operating device capable of identifying bubbles. Wherein the injector control module comprises a linear reciprocating motion mechanism and a dovetail clamp, the linear reciprocating motion mechanism is used for clamping a needle cylinder tail turnup of an injector, the linear reciprocating motion mechanism is connected with the dovetail clamp, the dovetail clamp is used for fixing the tail end of a push rod of the injector, and the linear reciprocating motion mechanism is used for driving the dovetail clamp to do reciprocating linear motion; the bubble detection module is connected with the injector control module and can rotate relative to the injector control module, and the bubble detection module is used for being arranged at the front end of the injector in a sleeving mode to recognize bubbles in the injector; the positioning and moving module is connected with the injector control module and used for driving the injector control module to move transversely, vertically and longitudinally and rotate around the longitudinal axis. According to the automatic medicine dispensing device, manual medicine dispensing operation is replaced by automatic mechanical operation, manual labor is saved, clinical working efficiency is improved, and safety is high.

The invention discloses a clinical urinary catheterization device for urinary surgery and a use method, and belongs to the technical field of medical instruments. Comprising a base, a rotating platform is arranged on the upper surface of the base, a plurality of collecting mechanisms are arranged on the rotating platform, opening and closing mechanisms are arranged above the collecting mechanisms, and an L-shaped supporting plate is fixedly connected to the right side of the outer side wall of the base; urine is temporarily stored through a plurality of collecting barrels, when one collecting barrel is almost full, a motor only needs to drive a rotating platform, the unoccupied collecting barrel is rotated to the position below a butt joint mechanism to complete switching, frequent dumping operation is not needed, meanwhile, a lifting plate of the butt joint mechanism is matched with a pulling plate and a first spring, butt joint and separation of an inserting pipe and a connecting nozzle can be rapidly achieved, and the working efficiency is greatly improved. The time investment of nursing personnel on urine treatment is greatly reduced, so that the nursing personnel can apply more energy to core nursing work such as illness state observation and medication guidance, and the overall clinical working efficiency is remarkably improved.

This application provides a configuration method and apparatus for a heart sound processing model based on multimodal knowledge distillation. It introduces knowledge distillation technology on the basis of deep learning-based heart sound data processing and builds a novel model configuration scheme in a deep and adaptive manner. This realizes the integration of multimodal training and lightweight deployment of knowledge distillation, so as to comprehensively improve the accuracy, stability and engineering usability of diagnosis, and has good application prospects in clinical work.

The invention provides an SPECT / CT-based renal function determination method and device and a processing system, designs a novel renal function determination architecture, and combines a CT structure image to more accurately distinguish kidney tissues and perirenal tissues and extract more real double-kidney signals compared with a traditional scheme that SPECT images are used for sketching double-kidney ROI (Region of Interest). The high time resolution and the high spatial resolution are both considered, so that the time radioactivity curve and the glomerular filtration rate of the separated kidney can be accurately measured, the high-quality measurement requirement for the separated kidney function in clinical work is met, and high-quality diagnosis and treatment service can be provided for a patient.

The invention relates to a bromhidrosis postoperative wound infection risk prediction method and a bromhidrosis postoperative wound infection risk prediction system, aims to solve the problems that an existing clinical evaluation method depends on subjective experience and lacks a standardized tool, and performs quantitative prediction on the individual infection risk of a patient by utilizing a column graph model constructed based on multi-factor analysis. The method comprises the following steps: systematically collecting clinical index data of a patient, wherein the clinical index data comprises general data and operation-related indexes; inputting the data into a pre-constructed column graph model, and obtaining a comprehensive risk score by matching a corresponding score for each index and performing accumulation; and finally, the risk level is divided into a low-risk class and a high-risk class according to a preset threshold value, and an intuitive basis is provided for clinical decision making. According to the method, the operation process is standardized, the result output is visual, the method can be effectively integrated into the clinical working process, and a practical auxiliary tool is provided for medical staff to identify high-risk patients and implement targeted prevention and nursing measures, so that the quality and efficiency of postoperative management are expected to be improved.

The invention discloses a perioperative delirium risk classification method and system for unbalanced medical data, and relates to the field of computer data processing and machine learning. Comprising the following steps: extracting relevant data of examination and surgical anesthesia of a patient, and marking relevant data corresponding to delirium; constructing a delirium risk classification model, inputting the marked related data into the delirium risk classification model, and training the delirium risk classification model by utilizing a method for dynamically adjusting a category balance factor and a classification difficulty factor; and inputting to-be-evaluated perioperative period patient data into the trained delirium risk classification model, and performing classification prediction on the delirium risk in the perioperative period. The gradient calculation process is reconstructed on the basis of the gradient boosting tree, the problem of model training deviation caused by scarcity of positive samples in medical data is solved, and doctors are assisted in efficiently completing scientific research and clinical work.

Embodiments of the present disclosure relate to customized machine learning training of radiotherapy clinics. Disclosed herein are methods for selecting and preparing patient data to facilitate the employment and custom training of machine learning models in a clinical environment, particularly for radiotherapy treatment planning. The disclosed embodiments simplify the customized training process through an automated workflow that includes pre-filtering patient metadata, retrieving related DICOM files, optional data anonymization, and generating training data. And organizing the data into a format suitable for machine learning training. The embodiments discussed herein reduce manual labor, minimize errors, and accelerate the integration of machine learning into the clinical workflow, enabling clinics to train and implement predictive models replicating specific clinical practices, thereby improving treatment accuracy and improving patient outcomes.

A method for execution by a computer includes detecting an object of a medical treatment environment based on environment signaling of the medical treatment environment to produce identified medical treatment devices and object profile information. The method further includes facilitating object tracking of the identified medical treatment devices within the medical treatment environment. The method further includes storing patient care tracking information for the identified medical treatment devices within a digital twin memory to facilitate subsequent management of patient care provided by the identified medical treatment devices that includes causing a clinical workflow de-assignment.

A clinical workflow escalation and acknowledgment governance system converts AI-assisted clinical outputs into governed workflow items. The system enforces execution-time routing, tiered escalation, and acknowledgment thresholds and stores immutable audit records. The invention improves safety and accountability without autonomously diagnosing conditions or prescribing treatment actions.

The invention relates to a medical alarm management method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining patient physiological data, medical equipment state data, clinical workflow information and patient basic information in real time, and generating a multi-dimensional data sequence on a unified time axis; inputting the multi-dimensional data sequence into an adaptive decision engine, dynamically adjusting an alarm triggering condition according to clinical workflow information, and generating an original alarm event when the triggering condition is met; carrying out root analysis on the plurality of original alarm events in a preset time, defining root events of the plurality of original alarm events, marking other original alarm events as derivative alarms, and packaging to form a nested alarm object; and correspondingly sorting the nested alarms according to the clinical emergency degree and the event sequence. According to the medical alarm management method and device, the computer equipment and the storage medium, the problems of alarm fatigue, information overload, unclear source, difficulty in tracing and the like in a traditional system can be fundamentally solved.