176 results about "Clinical work" patented technology

The invention discloses a cervical cancer close-range radiotherapy high-risk target area sketching method fused with a multi-modal image. The method comprises the following steps of collecting an MRI image scanned before radiotherapy and a CT image during radiotherapy of a cervical cancer close-range radiotherapy patient and annotation data of the MRI image and the CT image; the method comprises the following steps: preprocessing an MRI image scanned before radiotherapy and a CT image during radiotherapy, and converting annotation data into a three-dimensional tag image; on the basis of the preprocessed MRI image, the preprocessed CT image and the three-dimensional label image of the preprocessed MRI image, the preprocessed CT image and the three-dimensional label image of the preprocessed MRI image, registration of the MRI image and the CT image is conducted through a pre-constructed registration neural network model, feature extraction and fusion are conducted on the registered MRI image and the registered CT image through a pre-constructed high-risk target area automatic segmentation neural network model of a multi-scale cross-modal attention mechanism, and the high-risk target area automatic segmentation neural network model of the multi-scale cross-modal attention mechanism is obtained. Automatic delineation of a cervical cancer close-range radiotherapy high-risk target area is realized; according to the method, automatic segmentation of HR-CTV in close-range radiotherapy of cervical cancer is realized, high efficiency, accuracy and generalizability are realized, and intelligent support can be provided for clinical work.

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.

A smart intravenous (IV) pole is disclosed, designed to maintain communications and seamlessly integrate medical devices even as a patient is relocated. The IV pole includes at least one antenna, and a network interface adapted for seamless communication during patient movement. The IV pole also includes a circuitry configured to obtain patient data associated with a patient. The IV pole retrieves one or more electronic medical health records associated with the patient. The IV pole retrieves medical data associated with the patient. The IV pole applies artificial intelligence (AI) models to at least one of the patient data, the electronic medical health records, or the medical data. The IV pole generates alerts associated with a medical condition of the patient and renders the alerts. The IV pole ensures uninterrupted data connectivity, monitoring, and communication during and after relocation, enhancing patient safety and supporting dynamic clinical workflows in modern healthcare environments.

The invention relates to the technical field of cardiovascular disease diagnosis, and discloses a myocardial perfusion and survivability evaluation method based on cardiac ultrasound contrast intelligent analysis. The method comprises the following steps: firstly, acquiring cardiac ultrasound contrast dynamic image data and pre-processing the data, then performing myocardial region segmentation by adopting an improved U-Net network in combination with an attention mechanism and a dynamic region growing algorithm, and constructing a myocardial perfusion zoning model. Then, myocardial perfusion dynamic characteristics are extracted, key time sequence characteristics are screened, and a multi-modal fusion evaluation model is constructed to generate a myocardial survivability probability distribution diagram. And finally, performing quantitative evaluation based on the probability distribution diagram, outputting a myocardial perfusion defect index and a survivability score, and generating a visual three-dimensional evaluation report. The accuracy of myocardial perfusion and survivability evaluation is improved, multi-modal information is integrated, quantitative evaluation and visualization are achieved, model robustness and clinical working efficiency are improved, and powerful support is provided for diagnosis and treatment of cardiovascular diseases.

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 invention provides an ear endoscope image automatic description system based on a large language model, and the system comprises a data annotation module which carries out the annotation of an abnormal condition in an ear endoscope image, and converts the data of the ear endoscope image into a picture text pair data set; the model training module comprises a multi-modal large language model and is used for training the multi-modal understanding capability of images and texts of the model by using the picture texts; and the model reasoning module is used for reasoning the new ear endoscope image to obtain the text description of the ear endoscope image. According to the system, visual understanding and language generation capabilities of a large language model are combined, accurate otoendoscope image description can be automatically generated, and clinical work of otolaryngologists is effectively supported.

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.

The invention discloses a business-driven medical service item charging management quality control method and system, and belongs to the technical field of medical service management.The business-driven medical service item charging management quality control method and system comprise the following specific steps that firstly, a business dictionary and a commodity price dictionary are built, the business dictionary comprises business behavior entries, and the commodity price dictionary comprises a commodity price dictionary; the commodity price dictionary comprises publicized financial amount entries; 2, constructing a mapping relation, and enabling the business behavior entries to correspond to the financial amount entries; 3, instructions are obtained, each instruction corresponds to one business behavior entry, and after medical staff select the instructions, corresponding financial amount entries are obtained through mapping relation processing. According to the invention, the medical service charging management knowledge base is driven by combing the business, and the business is associated with the charge, so that the clinical satisfaction is improved, and the clinical staff can use more time to treat and cure the patient.

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 discloses a clinical medicine practice skill evaluation system, and relates to the technical field of clinical medicine education, and the system comprises the following components: a comprehensive data processing module which collects and preprocesses real patient electronic medical record data and examinee multi-modal data, fuses all modal data features, cleans the electronic medical record data, and stores the cleaned electronic medical record data; providing data for subsequent modules; the personalized intelligent virtual patient is generated based on the electronic medical record data of the real patient, rich and diversified clinical simulation scenes are provided for examinees, the complexity and diversity of the real patient are achieved, the illness state can be adjusted in real time according to decisions of the examinees, the uncertainty and complexity of the clinical scenes are simulated, and the clinical simulation experience of the examinees is improved. The system has the advantages that the system is simple in structure and convenient to use, clinical thinking of examinees can be cultivated and improved in practice, the examinees can learn to make accurate judgment and decisions when the illness state changes, and meanwhile, the examinees can exercise the strain capacity of the examinees through interaction with virtual patients so as to better adapt to various challenges in actual clinical work.

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 utility model discloses a medical multifunctional ruler, which belongs to the technical field of surgical clinical props and comprises a ruler body, and a length scale, a light-proof medicine allowance scale, a pupil size contrast scale, a thirst scale and a pain scale are carved on the ruler body. Functional components of a plurality of small tools are integrated on one ruler, the effects of diagnosing, treating and monitoring surgical diseases and symptoms can be achieved through the ruler, a nurse can conveniently and rapidly prize a cover of a liquid bottle through the arranged bottle opener, and the liquid bottle is convenient to use. The body condition of a patient or the implementation state of medical props is detected and observed through the length scale, the light-proof medicine allowance scale, the pupil size contrast scale, the thirst scale and the pain scale which are carved on the ruler, various tools needed in clinical work of nurses are integrated through the functional ruler, and the functional ruler is short, light, convenient to carry and high in practicability. And convenience is provided for clinical work of nurses.

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.

The present invention discloses an auxiliary analysis model for predicting corneal edema after phacoemulsification surgery for cataracts, which belongs to the field of medical technology. The model uses the best corrected visual acuity (BCVA) before phacoemulsification surgery and the cumulative released energy (CDE) during the phacoemulsification process during the surgery as indicators to construct a nomogram; wherein, the nomogram includes five line segments, each line segment is marked with a fixed scale, and the relative position of each line segment is fixed, and the five line segments are, from top to bottom, BCVA and CDE score line segments, BCVA value line segments, CDE value line segments, BCVA and CDE score total line segments, and corneal edema probability line segments; the prediction model of the present invention can complete relatively accurate predictions using only two common clinical data, has low data requirements for use, is convenient and practical, and has a high accuracy rate, can help ophthalmologists quickly and accurately judge the risk of corneal edema after phacoemulsification surgery, and assist ophthalmologists in making decisions in clinical work.