31 results about "Clinical case" patented technology

The invention relates to the technical field of medical health monitoring, and particularly discloses a chronic disease patient physical examination data and complication nursing monitoring system based on the Internet of Things, multi-dimensional physical examination data such as vital signs and blood biochemical indexes of a patient are collected in real time through a multi-source sensing equipment network, and an individualized data stream is constructed; extracting parameter collaborative change characteristics by adopting multi-time scale analysis, and constructing a dynamic physiological characteristic spectrum; identifying the abnormal offset by calculating the deviation degree of the feature vector distribution and the reference distribution; based on intelligent matching of the spatial distribution features of the feature vectors and a clinical case library, generating structured early warning information including risk assessment and personalized nursing schemes; and finally, visual display and preventive nursing intervention of the complication risk evolution process are realized.

The invention relates to the technical field of medical training equipment, in particular to a critical care ultrasonic image training system, which comprises a clinical data acquisition module for acquiring critical clinical case data, ultrasonic image materials and diagnosis and treatment process specifications; the training scene construction module is used for constructing a high-fidelity three-dimensional training scene according to severe clinical case data, ultrasonic image materials and diagnosis and treatment process specifications; the virtual ultrasonic practical operation module simulates the operation of an ultrasonic probe based on a high-fidelity three-dimensional training scene, and generates an ultrasonic image corresponding to an anatomical part in real time; the intelligent skill assessment center assesses operation normalization and diagnosis accuracy through practical operation data and real-time generation of an ultrasonic image corresponding to an anatomical site in combination with an improved ResNet-LSTM model, and an assessment result is obtained; and the personalized teaching unit generates a customized training scheme and knowledge strengthening content according to the evaluation result in combination with the learning track of the student. Therefore, the problems of insufficient dynamic scene simulation, poor authenticity and the like in the prior art are solved.

The application provides a rule cultivation quality full life cycle monitoring method and system, which comprises the following steps: in a training period, collecting operation logs of rule cultivation personnel in multiple clinical information systems, and reconstructing the operation logs into behavior trajectory sequences reflecting clinical core capabilities; evaluating the quality deviation degree of the rule cultivation personnel in the clinical case processing process based on the behavior trajectory sequences; obtaining the skill mastering vector of the rule cultivation personnel in each clinical core capability based on the quality deviation degrees of multiple clinical operations in a historical period and a preset capability dimension mapping rule; generating the capability evolution characteristics of the rule cultivation personnel in the training period according to the change law of the skill mastering vector over time; and generating a multi-dimensional evaluation result including skill maturity, risk deviation degree, diagnosis and treatment logic consistency and clinical efficiency factors based on the capability evolution characteristics and the quality deviation degree. The application improves the timeliness and accuracy of rule cultivation quality evaluation.

This application discloses a method and apparatus for constructing a Traditional Chinese Medicine (TCM) diagnostic and treatment knowledge model. The method includes: transforming a general-purpose basic language model into a model specifically for the TCM field to obtain a basic TCM model; controlling the obtained basic TCM model to learn diagnostic and treatment thinking within the TCM field to obtain a basic TCM diagnostic and treatment model; aiming to enhance the flexibility of logical reasoning in the obtained basic TCM diagnostic and treatment model, controlling the obtained basic TCM diagnostic and treatment model to learn the diagnostic reasoning paths of clinical cases in the TCM field to obtain a TCM reasoning diagnostic and treatment model; controlling the obtained TCM reasoning diagnostic and treatment model to learn the unique TCM knowledge and unique diagnostic and treatment thinking of a target renowned physician to obtain a unique TCM diagnostic and treatment model; and controlling the obtained unique TCM diagnostic and treatment model to favor the unique diagnostic and treatment thinking of the target renowned physician to obtain a TCM diagnostic and treatment knowledge model. This improves the diagnostic accuracy and clinical decision-making reliability of the model.

This application provides a method and apparatus for generating traditional Chinese medicine (TCM) prescriptions based on multi-task joint optimization. The method includes: constructing a training set based on historical clinical case data, the training set comprising multiple samples and sample weight labels, each sample containing clinical text features, TCM prescription labels, and prescription set labels; constructing an enhanced training set based on the training set; training a multi-task joint optimization prescription generation model based on the enhanced training set; predicting TCM prescription sequences using an autoregressive approach, with the TCM prescription labels as the supervision signal; a set prediction branch used to predict the presence or absence of each TCM herb in the global TCM dictionary based on the semantic representation of clinical text features, with the prescription set labels as the supervision signal, and introducing sample weight labels into its loss function to enhance attention to low-frequency TCM herbs; training the model by weighted fusion of the loss functions of the above two branches; and generating TCM prescriptions using the trained model.

This application provides a method, apparatus, device, and storage medium for self-correction of a medical visual language model based on a dynamic experience base (DEKB), relating to the field of medical visual language processing technology. The method includes: when the initial diagnostic result of the medical visual language model for a current clinical case does not match the fact label, constructing the current case as a structured experience unit and storing it in a dynamic experience knowledge base; upon receiving a query, retrieving historical experience cases related to the new query from the dynamic experience knowledge base; using the historical experience cases as contextual prompts to guide the medical visual language model in chain-like thinking, generating a corrected reasoning result. By constructing an endogenous dynamic experience knowledge base, designing a deep attribution analysis mechanism, and employing a dual-threshold retrieval algorithm, this application enables DEKB to transform the model's historical errors into structured knowledge that can be used for future reference, significantly improving the robustness and generalization ability of medical model image diagnosis reasoning.

The invention discloses an NK cell exosome, a preparation method thereof and application of the NK cell exosome in preparation of drugs for targeted treatment of rectal cancer through meridian points, and belongs to the field of biological medicine and traditional Chinese medicine. The invention provides a method for preparing a high-purity NK cell and a high-concentration and high-potency NK cell exosome. Experimental results show that the NK cell exosome obtained by the method provided by the invention can efficiently kill tumor cells and has dose dependence; animal experiments show that the NK cell exosome prepared by the invention can significantly inhibit tumor growth; clinical cases show that accurate targeted therapy can be realized through meridian point injection of the NK exosome, indexes of a rectal cancer patient are recovered to be normal, and clinical relief is realized. According to the invention, a modern exosome technology and a traditional Chinese medicine meridian point treatment method are combined for the first time, a cell derivative medicine for treating the advanced rectal cancer is provided, and a theoretical and practical basis is provided for clinical treatment of the advanced rectal cancer.

This invention provides a medical training system, comprising: a standardized feature library construction module, which breaks down target medical operations into multiple standard steps and defines a standard value range for each step; a competency standard library construction module, which defines multiple competency levels and associates them with corresponding target medical operations; a case provision module, which provides simulated clinical cases according to competency levels; an error recording module, which determines that an operation error is triggered when the monitored operation feature data deviates from the standard value range, and generates a personal error file; and a targeted training module, which, in response to a selection command, retrieves the training scenario of the operation error node and generates a specific training task for the operation error. Therefore, this invention establishes an objective, quantitative, and standardized operation evaluation system, transforming subjective operation evaluation into objective measurement, enabling graded judgment of operation compliance, reducing the subjectivity and variability of human evaluation, and improving the effectiveness of nurse training.

This application relates to the field of educational informatization technology and discloses an artificial intelligence-based virtual simulation teaching system for medical physiology, comprising: a system for collecting, processing, and encrypting and storing multi-source teaching data, including job requirement data, student operation data, voice interaction data, and clinical case data; a virtual simulation teaching module for constructing virtual diagnosis and treatment scenarios and conducting simulation teaching; a behavior analysis and demand adaptation module for correlating and analyzing job requirement data and learning behavior data, and outputting a behavior analysis report; a moral education evaluation module for quantifying medical ethics elements into constraint indicators and generating a moral education evaluation report in conjunction with the behavior analysis report; and an industry-education collaboration module for establishing a data transmission channel, accessing external data to update the simulation scenario, and enabling two-way interaction of teaching and evaluation-related data. This application improves the adaptability and evaluation accuracy of medical virtual simulation teaching.

The invention provides a processing method and device for clinical cases, and the method comprises the steps: generating a unique hash value through a first fingerprint feature vector corresponding to a fingerprint of an uploaded user and a first identification code configured for a target clinical case when the target clinical case is uploaded, and then obtaining a determined first random sequence, and determining characters needing to be replaced in sensitive fields in the target clinical case according to the first random number sequence, selecting a first target character from a character candidate set configured for the characters needing to be replaced according to the first random number sequence, and replacing the characters needing to be replaced by using the first target character, by means of the method, encryption can be completed, sensitive information can be hidden, the integrity and readability of data are not damaged, and the value of the clinical case during secondary utilization is improved.

The invention discloses a medical examination report analysis system and method based on big data, and relates to the technical field of medical data processing, the system comprises a data acquisition module, a preprocessing module, a storage module, an index correlation analysis module, an abnormity early warning module, a result generation module and a user interaction module, and the method comprises corresponding data processing and analysis steps. Multi-source data such as inspection reports, historical diagnosis and treatment, clinical cases and the like are collected through a standardized interface, are subjected to cleaning, standardization and structural conversion, and are accessed by means of a distributed storage architecture; an Apriori association rule algorithm is adopted to mine index association, a random forest and a neural network model are combined to realize risk assessment, and a three-level grading early warning mechanism is matched to push accurate suggestions. According to the method, traditional manual interpretation is replaced, the analysis efficiency and accuracy are improved, the problems of insufficient associated information mining, non-uniform diagnosis standards and the like are solved, medical institution scenes at all levels are adapted, interactive optimization is supported, clinical precise diagnosis is assisted, the burden of doctors is relieved, and the method has important popularization value for intelligent application of medical data.

The application discloses a rehabilitation auxiliary tool evaluation method based on multi-agent and RAG technology. The method comprises the following steps: constructing a multi-agent system, including a rehabilitation doctor agent, an auxiliary tool engineer agent, a nursing staff agent and a user interaction agent; building a dynamic knowledge base based on RAG technology, including an auxiliary tool product database, a rehabilitation medical knowledge base, a clinical case database and an industry standard database; interacting with the user, and dynamically adjusting the questioning method, language style and question order according to the user type and answer content; retrieving in the dynamic knowledge base according to the obtained information, and respectively outputting professional evaluation opinions; and integrating the professional evaluation opinions of the rehabilitation doctor agent, the auxiliary tool engineer agent and the nursing staff agent according to a collaborative decision-making model to generate a multi-dimensional auxiliary tool evaluation report and a recommended scheme. The above method can make the evaluation process of the auxiliary tool more efficient, and the evaluation result more accurate and effective.

This invention provides a management system for non-invasive prenatal testing (NIPT), comprising the following modules: a case classification module for recording and classifying NIPT results; a follow-up form module for creating follow-up forms based on the results from the case classification module for tracking and monitoring; a data statistics module for automatically statistically analyzing the results from the follow-up form module and calculating NIPT performance indicators; a data center module for managing all NIPT results and improving the follow-up system; and a case learning module for acquiring NIPT result data from the follow-up form module and recording classic clinical cases to support case discussions and form a closed-loop testing system. This management system for NIPT, by constructing a closed-loop management system for the entire NIPT process, integrates multi-source data from testing and follow-up data to form a closed-loop management system for prenatal testing.

The invention provides a traditional Chinese medicine clinical curative effect data acquisition device and analysis method based on multi-channel detection, and relates to the field of medical instruments. The traditional Chinese medicine clinical curative effect data acquisition device based on multi-channel detection comprises a multi-channel synchronous acquisition module, a traditional Chinese medicine component extraction module, a data preprocessing module, a core analysis module, a terminal display module and a data storage module. According to the invention, the functions of multi-channel extraction and quantitative detection of effective components of traditional Chinese medicines are effectively integrated, standardized detection of process parameters and component contents in a pilot test stage is realized, the effects of detection precision and standardization similar to those of western medicine pilot tests are achieved, and a standardized traditional Chinese medicine clinical case data acquisition system is constructed; synchronous acquisition of case basic information, curative effect indexes and component metabolism data is realized, and the problem of data fragmentation is solved.

The application discloses a glioblastoma peritumoral tumor infiltration segmentation model, which comprises clinical case collection, image information collection, pathological information collection, image data preprocessing, image feature learning based on CPC for self-learning of a Gb peritumoral edema region, migration learning by using a 3DUX-Net segmentation model, construction of a peritumoral infiltration segmentation model, and segmentation model verification. The application learns the artificial ROI segmentation features, establishes the peritumoral infiltration segmentation model, verifies the effectiveness of the model through double-blind testing, and accurately segments the peritumoral tumor infiltration through the peritumoral infiltration segmentation model, thereby providing an important reference for clinical multidisciplinary diagnosis and treatment.

The application provides a three-dimensional reconstruction optical navigation method and device for an electronic choledochoscope, and the navigation method specifically comprises the following steps: S1, extracting MRCP images of a patient meeting a condition from a clinical case library for depth processing and data labeling; S2, importing the labeled data into a liver and gallbladder three-dimensional reconstruction system to reconstruct a liver, a bile duct tree and a stone; S3, taking a target stone bile duct as a terminal point to calculate a shortest and safest three-dimensional channel from a laparoscope bile duct incision or a needle insertion point on the skin to the bile duct; S4, inserting a marked choledochoscope into the bile duct; S5, entering a double image fusion navigation mode; S6, performing puncture until the tip of the choledochoscope accurately reaches a target bile duct stone position; and the like. The application can lock and mark an intrahepatic target bile duct and a stone position before surgery, and reconstruct a three-dimensional map, so that the choledochoscope can be guided by the three-dimensional map to quickly enter the target bile duct after entering the intrahepatic bile duct, and the surgery and stone removal efficiency are improved.

This application provides a catheter assembly and a carotid artery bypass system. The deformable tube has axial telescoping function, and the deformable part is movably sleeved on the outside of the deformable tube. The distal end of the deformable part is connected to the deformable tube and the inner catheter, and the proximal end of the deformable part is connected to the deformable tube and the outer catheter. The deformable part has a contracted state and an expanded state. When the above-mentioned carotid artery bypass system is inserted into the artery, the operator can actively control the shortening of the deformable tube at an appropriate time, thereby increasing the effective working window of the common carotid artery segment. The wide range of telescoping can dynamically match the length of the common carotid artery lesion, covering most clinical cases of carotid artery stenosis. In addition, the operator can also actively control the contracted and expanded states of the deformable part at an appropriate time, using the expanded state of the deformable part to properly fit the inner wall of the blood vessel, forming a mechanical anchoring point on the inner wall of the blood vessel, effectively solving the problem of unexpected slippage of the carotid artery nerve protection system relative to the common carotid artery.

The application provides a magnetic resonance cholangiopancreatography data labeling method, a training model and an intelligent navigation system, and specifically comprises the following steps: S1, extracting MRCP images meeting the conditions from a clinical case library; S2, converting original DICOM format images into two-dimensional image formats, and performing deep processing on the two-dimensional images; S3, using LabelMe as a labeling tool to perform region delineation on the two-dimensional images; S4, frame-by-frame checking the labeled boundaries; S5, independently auditing the labeling results; S6, calculating the consistency index between labelers; S7, storing the labeling files that pass the audit in correspondence with the original images to form a standardized data set; and the like. The application can quickly and accurately construct a bile duct labeling data set with clear structure, accurate boundary and clear pathological characteristics, and provides solid data support for subsequent automatic segmentation, bile duct structure modeling and disease auxiliary diagnosis based on artificial intelligence.

Methods to enhance the computational localization of cardiac arrhythmia sources are provided. A method may include receiving, from a first user, clinical data associated with a clinical case. The clinical data may include a patient anatomic information, diagnostic and / or treatment modalities, treatment parameters, treatment outcome, and medical literature. The clinical case may be indexed based on a first plurality of characteristics associated with the clinical data. The indexing may include associating at least a portion of the clinical data with a computational simulation of cardiac arrhythmia having a second plurality of characteristics matching the first plurality of characteristics. At least a portion of the clinical data associated with the indexed case may be provided to a second user in response to a query from the user. Related systems and articles of manufacture are also provided.

This invention provides a collaborative reasoning diagnostic assistance method and system, relating to the field of large-scale model technology. First, a knowledge base of clinical cases of birth defects in children, containing medical reasoning rules, is constructed. Then, multimodal diagnostic information of a target child is received and decomposed to obtain the decomposed results. The decomposed results of the target child's multimodal diagnostic information are dynamically correlated and reasoned with the case data and medical reasoning rules in the knowledge base of clinical cases of birth defects using a teaching large-scale model, generating a structured differential diagnosis opinion, including the defect type, medical evidence chain, and feature matching. The structured differential diagnosis opinion is pushed to the clinician's terminal, feedback is collected, and the reasoning parameters of the teaching large-scale model and the knowledge base rules are collaboratively adjusted. This invention can comprehensively utilize multimodal information, improve diagnostic accuracy and reliability, and can be continuously optimized and improved.

The application discloses a marker tiRNA-Gln-TTG-001 and application thereof, and belongs to the technical field of biotechnology and molecular diagnosis. The applicant finds that, compared with lung cancer patients without brain metastasis, tiRNA-Gln-TTG-001 is significantly highly expressed in the peripheral blood circulation of lung cancer patients with brain metastasis, which provides an important basis for the marker as a specific plasma marker for predicting, monitoring or diagnosing lung cancer brain metastasis. The new clinical cases are selected for verification, and the results show that tiRNA-Gln-TTG-001 can be used as a specific metastasis marker for lung cancer brain metastasis, which opens up a new non-invasive, convenient and specific detection way for early prediction, dynamic monitoring, diagnosis and efficacy evaluation of lung cancer brain metastasis.

The soft tissue puncture interventional surgical robot provided by this invention includes an end-effector connected to the end of a robotic arm. The end-effector includes a mounting base and an arc-shaped positioning module connected to one side of the mounting base with an arc-shaped guide rail. By connecting an ultrasound probe positioning and multi-dimensional sensing module to the bottom of the mounting base and extending downwards, the rotational positioning and puncture guiding module includes a puncture guiding component and a rotational positioning module. The puncture guiding component is configured to hold the puncture needle and be rotatable. The rotational positioning module is slidably mounted on the arc-shaped guide rail to drive the rotation of the puncture guiding component. The rotation direction of the puncture guiding component is perpendicular to the sliding direction of the rotational positioning module. This allows for real-time feedback of ultrasound images during surgery, displaying the lesion and puncture needle position. It also provides the puncture guiding component with two degrees of freedom, resulting in a larger relative range of motion and angle, supporting intraoperative ultrasound adjustment and secondary puncture planning. This robot is applicable to most clinical cases.

The invention belongs to the technical field of medical teaching models, and particularly relates to an interactive human anatomy head and neck venous return model and a display method thereof. The model comprises a locally transparent head and neck model and a control base. A plurality of LED flexible light bars are arranged in the model according to an anatomical path and are used for simulating main vein blood vessels such as a head-arm vein, an internal jugular vein, a facial vein and a cavernous sinus. According to the control module, through the user interface design of a liquid crystal screen, on one hand, a structural flow chart is organized according to the time-space sequence of venous return, and the navigation effect of autonomous learning of students is achieved; on the other hand, the on-off, the flowing direction and the time sequence of each light bar can be independently controlled through a text button on the liquid crystal screen, so that the vein blood flow direction is dynamically demonstrated. The model can also visually display related clinical cases through touch pressure feedback, can dynamically display the blood flow direction, supports interactive operation, can simulate the clinical pathological process, and is higher in interactivity.

The invention discloses an automatic three-dimensional evaluation system for oral operation based on a Gaussian splashing technology, and relates to the cross technical field of medical image processing, computer vision and oral medicine education, the system comprises six core modules, a student end acquisition module supports mobile terminal multi-view image and video acquisition and oral scanning data uploading; the scene preprocessing module carries out standardization processing on the collected data; the Gaussian splash three-dimensional reconstruction module generates a three-dimensional model with real textures based on the camera pose and the image data; the preparation quality evaluation module realizes automatic scoring and visual feedback through model registration and difference quantification; the clinical case teaching library module realizes structured storage and retrieval of case models and related information; and the interactive display module supports cross-terminal model operation, annotation and remote recheck. The system does not need high-end equipment, realizes automatic and standardized evaluation of oral operation, adapts to multi-scene teaching requirements, and improves evaluation efficiency and consistency.

The invention discloses application of lncRNA AC022031.2 in prognosis evaluation or treatment of gastric cancer, and belongs to the technical field of biomedicine. The invention provides a detection tool for predicting prognosis of gastric cancer, and also provides a pharmaceutical composition for treating gastric cancer. The application proves that the lncRNA AC022031.2 can be used for effectively predicting the prognosis of the gastric cancer by combining bioinformatics analysis with clinical cases. Cell experiments prove that the interference of the lncRNA AC022031.2 can effectively inhibit the migration and invasion ability of gastric cancer cells, and the expression of the targeted interference of the lncRNA AC022031.2 can achieve the effect of treating the gastric cancer. The application provides a new direction for precise medical treatment of gastric cancer clinically.

Methods to enhance the computational localization of cardiac arrhythmia sources are provided. A method may include receiving, from a first user, clinical data associated with a clinical case. The clinical data may include a patient anatomic information, diagnostic and / or treatment modalities, treatment parameters, treatment outcome, and medical literature. The clinical case may be indexed based on a first plurality of characteristics associated with the clinical data. The indexing may include associating at least a portion of the clinical data with a computational simulation of cardiac arrhythmia having a second plurality of characteristics matching the first plurality of characteristics. At least a portion of the clinical data associated with the indexed case may be provided to a second user in response to a query from the user. Related systems and articles of manufacture are also provided.

This invention discloses a headache risk assessment system and its usage method, specifically relating to the field of medical testing technology. This invention achieves stratified, quantified, and objective assessment of headache risk, addressing the pain point of traditional assessments relying on subjective feedback. It stratifies by gender and age range, constructs a stratified reference control set based on the mean laboratory indicators of healthy controls, and generates a specific threshold control table by combining headache subject data, ensuring the assessment results align with the physiological characteristics of different populations. Simultaneously, it transforms laboratory test indicators into calculable risk coefficients, replacing traditional subjective scales. This achieves early objective screening of asymptomatic individuals, improves the relevance, accuracy, and repeatability of the assessment results, and reduces the risk of missed or misdiagnosed clinical cases.

The invention discloses a medical information learning auxiliary system based on a knowledge graph, and the system comprises a relation information construction module which is used for obtaining medical theoretical information, extracting the relation between entities, and constructing a theoretical knowledge graph; the perception aggregation module is used for inputting clinical case information, extracting a relationship between entities and constructing an application knowledge graph; the fusion module fuses the theoretical knowledge graph and the application knowledge graph based on the semantic features to generate a fused knowledge graph; and the information output module retrieves and outputs pre-selected information from the fused knowledge graph according to the information input by the user. In the technical scheme provided by the invention, repeated and redundant contents are effectively eliminated through semantic fusion.