57 results about "Medical screening" patented technology

A large language model-based medical examination conclusion generation method includes: obtaining a target manifestation text corresponding to a target medical examination; extracting medical examination inference knowledge that matches the target manifestation text from a medical examination inference knowledge base, where the medical examination inference knowledge includes a manifestation text and a conclusion text corresponding to a medical examination; constructing a sample based on the extracted medical examination inference knowledge, and constructing a prompt text based on the sample and the target manifestation text; and inputting the prompt text into a large language model, and outputting, by using the large language model, a target conclusion text that corresponds to the target medical examination and that is obtained by performing inference based on the target manifestation text and under guidance of the sample.

The invention discloses an information processing method and device for examination item recommendation, equipment and a medium, relates to the technical field of medical data processing, is applied to a computer device and comprises the steps that key feature vectors in health information of a target object are extracted; querying an initial disease name and an initial confidence coefficient corresponding to the vector from a medical knowledge graph; according to the initial disease name and the initial confidence coefficient, generating a health state evaluation list which corresponds to individual attribute information in the health information and comprises a target disease name and a corresponding target confidence coefficient; generating a preliminary recommendation table of the target object based on the health state evaluation list, wherein the recommendation table comprises initial medical examination items sorted based on the target confidence; and optimizing the preliminary recommendation table according to the evaluation information and the individual attribute information of each initial medical examination item to obtain a target recommendation table containing the target disease name and the corresponding target medical examination item. And personalized and high-accuracy medical examination item recommendation is realized.

The application relates to the technical field of data processing, and discloses an old person health state evaluation data processing system based on multi-modal data, which comprises a medical data integration module, an across-modal causal fusion processing module, a health state evolution modeling module, a backtracking evaluation report module and a decision output module. The medical data integration module acquires electronic medical record data and medical examination reports through a FHIR interface and extracts structured health indexes. The across-modal causal fusion processing module fuses monitoring data and medical texts through an image, a text and an image sandwich architecture. The health state evolution modeling module maps a health feature vector into three-dimensional state indexes of physiological functions, cognitive levels and motor abilities. The backtracking evaluation report module and the decision output module are used for backtracking evaluation and decision output. Through the image, the text and the image sandwich architecture, deep semantic fusion of multi-modal features is realized under the constraint of medical pathology rules, feature weight adaptive distribution is dynamically guided based on a medical causal graph, a high-dimensional fusion vector retaining key pathological information is generated, the semantic integration capability of health data is significantly improved, and the reliability of discrimination and decision is improved.

Provided herein are computerized system and method for full patient flow management through an emergency department process, integrating multi-agents LLM. The system and method utilize a plurality of LLM-based agents configured to perform one or more of: extract relevant medical information and generate a summarized medical history; interactively questioning the subject regarding its medical history and regarding the main complaint(s); provide recommendations regarding various medical examinations; process the summarized medical history and the results of the recommended medical examination(s) and; provide further summary, recommendations or instructions, regarding diagnosis and a decision regarding discharge or admission of the subject.

The invention relates to the technical field of medical instruments, and discloses a disinfection device for a reproductive medicine examination room, which comprises a flowing gas heating mechanism and a rotary reciprocating shaking mechanism, a lower movable disc which is positioned in the vertical disinfection barrel and can rotate, an upper movable disc which is positioned right above the lower movable disc and can generate a longitudinal reciprocating motion effect, and a storage movable plate which longitudinally moves along with the upper movable disc and can support an instrument are arranged in the vertical disinfection barrel. According to the disinfection device for the reproductive medicine examination room, an instrument is effectively disinfected through disinfection gas, the disinfection gas is gas and has the rapid movement and permeation functions, in addition, the instrument can shake in the disinfection process through the device, the instrument can generate a movement gap through shaking, and therefore the instrument can be disinfected conveniently. And the disinfection gas can generate a flowing disinfection effect along the whole surface of the instrument, so that the disinfection range of the instrument is expanded, and the infection risk of the instrument in the subsequent use process is reduced.

The invention discloses a full-cycle management method for an endometriosis patient, and relates to the technical field of medical informatization decision making, and the method comprises the steps: collecting the preliminary diagnosis disease staging information, lesion feature text and laboratory inspection data of the patient, and generating a case data set through medical term standardized conversion and text structured processing; constructing a recurrence risk prediction model, inputting the case data set into the recurrence risk prediction model, and generating a recurrence risk quantitative score; adjusting a follow-up period based on the recurrence risk quantitative score, setting follow-up time nodes and medical examination items, and combining to generate a follow-up plan; and performing graded reminding based on the follow-up visit plan, and collecting symptom scoring records, medicine use data and life quality evaluation results submitted by the patient to form a follow-up visit data set. The dynamic follow-up visit plan is generated by constructing the recurrence risk prediction model, individualized follow-up visit management is achieved, and the problem that follow-up visit depends on static experience and cannot be matched with a real risk level is solved.

The application relates to the technical field of ultrasonic image analysis, and discloses a thyroid nodule evaluation system based on ultrasonic images. The system obtains medical record data and medical examination data of a patient through a multidimensional acquisition module, classifies and forms a data set, analyzes the thyroid function state of each patient through an intelligent evaluation module, generates a function coefficient, analyzes the picture quality of each group of ultrasonic images again, generates corresponding detection data group Jcsj, establishes a unified evaluation standard, quickly screens out key frames from a large amount of ultrasonic image data, has high multidimensional integration efficiency, sets a fixed range threshold value for the intelligent evaluation module, analyzes and generates a nodule volume and a nodule score in combination with a medical data set, and in combination with the function coefficient, the detection data group and the nodule score, evaluates the risk grade of the thyroid nodule and the picture quality of the ultrasonic image of the patient, screens out key frames of the ultrasonic image, and outputs a treatment suggestion; and the intelligent evaluation has high precision.

The application discloses a kind of compound screening method and system for regulating blood-brain barrier permeability, it is related to medical screening technical field, the specific steps of the method are as follows: S100, collect blood-brain barrier related cell multi-omics data to form original set;S200, data is preprocessed and standardized;S300, molecular network is constructed by cross-omics analysis, and key target is screened;S400, target information is integrated to establish structured target pool;S500, effective compound for regulating blood-brain barrier permeability is screened out by molecular docking and primary cell verification, the application constructs gene-protein-metabolite network by multi-omics integration and cross-omics analysis, accurately identifies blood-brain barrier key target, provides high credibility target pool;Combined with molecular docking and primary cell mixed culture verification, realize efficient screening and functional safety evaluation of candidate compound, significantly reduce research and development cost, provide efficient technical path for drug research and development.

The embodiment of the invention provides a physiological age prediction method and device, equipment and a storage medium, relates to the technical field of computers, can realize accurate prediction of physiological age by integrating external display images and internal medical examination data of human beings, and realizes efficient prediction calculation without contacting a detected person. The method provided by the embodiment of the invention comprises the following steps: acquiring face image data of a detected person, examination data of at least one human body physiological index and a real age; detecting a wrinkle area from the face image data, and determining an appearance aging factor of the detected person according to the detected wrinkle area; determining a body aging factor of the detected person according to the examination data; and obtaining a physiological age prediction result of the detected person according to the appearance aging factor, the body aging factor and the real age.

An image processing apparatus includes: a processor; and a memory connected to or built in the processor. The processor is configured to generate, as learning data used for training a machine learning model for medical images and examination results of medical examinations, new medical images from a first medical image and a second medical image among a plurality of the medical images according to a generation condition, and generate new examination results by performing calculation based on the generation condition on a first examination result of the medical examination corresponding to the first medical image and a second examination result of the medical examination corresponding to the second medical image.

A glove that includes a set of electrocardiogram leads coupled to the glove and configured to record a 12-lead electrocardiogram by contacting a body of a user with the set of electrocardiogram leads. The set of electrocardiogram leads include precordial leads that contact a chest of the user and are positioned along a peripheral edge of the glove that connects a palmar side of the glove to a dorsal side of the glove. The set of electrocardiogram leads also includes a first arm lead that is configured to contact a first arm of the user and is positioned on the palmar side of the glove spaced apart from the peripheral edge. Additionally, the set of electrocardiogram leads includes a second arm lead that is configured to contact a second arm of the user and is positioned on the dorsal side of the glove spaced apart from the peripheral edge.

The invention discloses a small animal medical examination fixing system and a using method.The small animal medical examination fixing system comprises a cylindrical structure, a partition plate, a spiral downward pressing structure, a foot sleeve, a supporting frame and a locking structure, the cylindrical structure is rotatably connected to the supporting frame and can be opened and closed, the partition plate is arranged in the middle of a cylinder and used for partitioning space, and the spiral downward pressing structure is arranged in the middle of the partition plate; meanwhile, supporting is provided for fixing the feet of the small animal, and the spiral pressing structure is used for fixing the body of the small animal. The device is simple in structure and convenient to operate, a small animal can be easily placed by opening the cylindrical structure, the process of fixing the small animal is simple, convenient and rapid, the fixing effect is good, legs of the small animal can be effectively fixed through the foot sleeves, the body of the small animal can be fixed through the spiral pressing structure, the small animal is prevented from moving in the scanning process, the quality of a scanned image is guaranteed, and the working efficiency is improved. The cylindrical structure is rotatable and adjustable in angle, and can be locked through the locking structure, so that the scanning angle of the small animal is convenient to adjust, and comprehensive and accurate scanning is ensured.

The application provides an inpatient hospital infection case identification method and system based on an AI large model, comprising: constructing a screening standard knowledge base based on infection sites, clinical diagnosis, etiological diagnosis and supplementary notes; collecting desensitization diagnosis and treatment data of inpatients, splicing with prompt words to form input text; calling a large model interface to process the input text of the inpatients, and the large model performs reasoning according to the screening standard knowledge base; analyzing the structured data returned by the large model to obtain infection early warning information; wherein the infection early warning information comprises: whether to be infected, infection site, risk level, key evidence and reference standard. The application can provide an inpatient hospital infection case identification method capable of improving the accuracy and scientificity of hospital infection screening, analyzing complex medical screening logic and providing key evidence with clinical interpretability.

The invention discloses a flight personnel health management method and system for vestibular function inspection abnormity, and relates to the technical field of flight personnel management, and the management method comprises the steps: obtaining a multi-source health data set of a target flight personnel, constructing a load characteristic variable, and carrying out the synchronous storage; according to the load characteristic variables, performing screening normalization processing action, and inputting the processed data to a pre-constructed linear evaluation model; according to the technical key points, a linear weighting model is adopted in the operation management method, the initial flight adaptability is output, and a flight adaptability threshold value is set, so that on one hand, rapid grading and discrimination of the health adaptability of the flight personnel are realized, and the continuous operation efficiency of the high-confidence flight adaptability personnel is guaranteed; and on the other hand, the preliminary evaluation mechanism is used as a condition triggering tool, and related processes of VEMP supplementary inspection are activated under corresponding conditions, so that the problems of low efficiency and overweight medical burden caused by one-time cutting in traditional medical screening are solved, and the effects of on-demand detection and accurate starting of resource optimization configuration are achieved.

1. The name of the design product: medical CT scanner. 2. The use of the design product: the design product is a CT scanner for medical examination. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: design 3 perspective view 1. 5. Design 3 is designated as the basic design.

Provided herein are computerized system and method for full patient flow management through an emergency department process, integrating multi-agents LLM. The system and method utilize a plurality of LLM-based agents configured to perform one or more of: extract relevant medical information and generate a summarized medical history; interactively questioning the subject regarding its medical history and regarding the main complaint(s); provide recommendations regarding various medical examinations; process the summarized medical history and the results of the recommended medical examination(s) and; provide further summary, recommendations or instructions, regarding diagnosis and a decision regarding discharge or admission of the subject.

The embodiment of the invention provides a method for generating information, a medical device and a non-transient computer readable medium. The information generation method comprises the following steps: receiving electronic data of a first medical examination report; analyzing the content of the first medical examination report according to the electronic data; and generating report information according to the analysis result, wherein the report information is used for generating a second medical examination report. According to the method, the operation of manually editing a template or an examination protocol of a medical examination report by a doctor can be saved, and the working efficiency is improved.

The disclosure provides an intelligent processing of medical screening conditions, and relates to the technical field of data processing, in particular to the technical field of medicine, databases, data queries and the like. The specific implementation scheme is: performing semantic intention analysis on a natural language description of a medical screening condition input by a user, and converting the natural language description into a structured intermediate representation, wherein the intermediate representation includes a plurality of structured condition units and their logical relationships, and one structured condition unit corresponds to one medical screening condition; based on a preset medical field knowledge ontology library, traversing each structured condition unit of the intermediate representation, and converting the intermediate representation into an executable database query statement based on the traversal result; executing the database query statement to obtain a data result; and generating explanatory evidence information connecting the natural language description and the data result according to the association information of the intermediate representation and the database query statement execution process.

The utility model relates to the technical field of medical screening turntables, and provides a children psychological behavior development problem early warning sign screening turntable which comprises a base and a supporting frame fixed to the upper surface of the base. A fixing shaft is fixed to the upper end of the supporting frame, an inner disc is rotationally connected to the fixing shaft, and an outer disc is fixedly connected to the end of the fixing shaft. An age scale circular ring, an early warning sign content ring and a circular blank area which are concentric are sequentially arranged on the side face, facing the outer disc, of the inner disc from outside to inside. According to the early-warning sign screening turntable for the psychological behavior development problem of the child, when the child is screened, the inner disc is rotated, so that the fan-shaped window of the outer disc corresponds to the corresponding age of the child, and the content, needing to be screened, of the child of the corresponding age is exposed, so that a doctor can watch and carry out screening work very conveniently; moreover, parents can conveniently watch early warning signs of children of different ages and have certain understanding of autism signs.

A medical examination-oriented real-time voice stream key information extraction method belongs to the technical field of artificial intelligence and medical information, and is characterized in that non-sensitive medical corpus and general corpus collection are combined with a style-oriented prompt control mechanism to drive a large language model to generate diversified simulation corpus, and an extended basic corpus set in the field of medical examination is constructed; the corpora are normalized and screened, and a high-quality corpus training set is formed; constructing a probability language model oriented to the field of medical examination based on the training set; detecting the medical examination real-time voice stream, abandoning mute segments, and forming an effective voice audio set; generating a candidate transcription sequence and an acoustic probability score for each speech segment by using an acoustic decoder; performing comprehensive scoring and sorting on the candidate sequences, and outputting an optimal transcription text; and extracting the structured medical examination key information from the transcriptional text by using a large language model. The medical term and numerical value recognition accuracy is high, and reliable support is provided for electronic medical record automatic input and report generation.

The invention relates to the technical field of medical examination report processing, in particular to a medical examination report processing method. The method comprises the following steps: extracting a value corresponding to a preset keyword from a target medical examination report, and adding the extracted value corresponding to the preset keyword to a first list; processing the first list by taking the record in the first list as a unit to obtain a second list; for any record in the second list, determining an output template corresponding to the record selected from a preset output template library according to the comprehensive keyword included in the record, and writing a value of the comprehensive keyword included in the record and a value of a preset keyword corresponding to the comprehensive keyword into the output template corresponding to the record, and obtaining an output text corresponding to the record. According to the method, the medical examination report can be converted into the text with higher readability, and the efficiency of manually obtaining the required information is improved.

A system and method can collect and store urine without invasive medical procedures while maintaining its sterile condition for medical examinations. The system includes an absorbent member for collecting urine. The system may further include an extraction system. The system can also comprise a tester. For example, the tester may include an indicator (e.g., a test strip and / or a rapid diagnostic test) and / or a sensor, and / or an automated tester.

A method for medical examination, in particular determination of the blood pressure of an animal that preferably has a paw and is in particular an animal of the subfamily of the Felinae. In the method, a curve comprising information about the arterial blood flow of the animal, in particular a photoplethysmogram, is recorded, and the curve is cut into several curve sections in such a way that each curve section corresponds to a heartbeat. According to another independent aspect, a sensor or a subset of sensors is selected from several sensors of the same kind to perform the examination.

The application discloses a kind of multi-granularity knowledge graph assisted diagnosis methods based on DeepSeek and Agent, comprising the following steps: step 1: receiving the electronic medical record text data and medical image data of patient;Step 2: construct knowledge graph;Daily update knowledge graph to reflect the latest medical research results;Step 3: by DeepSeek-R1 analysis electronic medical record text data;Step 4: by multilayer three-dimensional convolution kernel extraction medical image data's spatial structure feature section;By Vision Transformer, medical image data is segmented into sequence block;Step 5: the output of DeepSeek-R1, multilayer three-dimensional convolution kernel and Vision Transformer is input to multimodal fusion module;Step 6: output high confidence diagnosis conclusion and probability distribution;Step 7: generate the intelligent report of structured text.The method of the application, by combining natural language processing, computer vision and knowledge graph technology, realizes accurate, efficient medical examination.

The invention relates to the technical field of data processing, in particular to a system and a method for auxiliary analysis of hormone-sensitive chronic cough, and the method comprises the following steps: collecting target indexes of a patient, including allergic disease history, sour regurgitation heartburn symptom, hematophilic granulocyte count, CRP, IgE, FEV1 / FVC and FeNO; preprocessing the target index to obtain a preprocessed index; and generating a risk score corresponding to the hormone-sensitive chronic cough according to the pretreatment index. In order to solve the problems that in the prior art, hormone-sensitive cough diagnosis indexes need to depend on a complex detection instrument to be collected, and implementation is difficult, on the basis of regression analysis, the indexes of auxiliary analysis are determined to be clinical data which can be obtained easily based on clinical symptoms, blood routine indexes, lung function examination and the like of a patient, and the hormone-sensitive cough diagnosis indexes are obtained. And a related auxiliary analysis system is established, so that complex instruments required in the traditional medical examination process are omitted, and the medical examination process can be quickly completed in any level of medical institutions.

1. Name of the product in this design: Laparoscope. 2. Intended use of this design: Laparoscope for medical examination. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention provides a lung cancer risk prediction method and system based on physical examination multi-time-point blood examination index modeling. The method comprises the following steps: extracting statistical time sequence characteristics and trend time sequence characteristics of a preprocessed physical examination data set; the statistical type time sequence features, the trend type time sequence features and basic information in the preprocessed physical examination data set conform to one another according to unique identification of the patient and form a unified data matrix; using the unified data matrix to train a random forest model, and using the trained random forest model as a lung cancer prediction model; and inputting the unified data matrix of the target subject into the lung cancer prediction model to obtain the lung cancer prediction probability output by the lung cancer prediction model. In the random forest model training process, the node splitting is classified by adopting the splitting criterion with the prior recall rate, the splitting index can be preferentially optimized for the medical screening scene, the false positive is balanced while the recall rate is ensured, and the sensitivity of the random forest model to the early case is improved.

The invention discloses a compound screening method and system for regulating and controlling permeability of a blood brain barrier, and relates to the technical field of medicine screening, and the method comprises the following specific steps: S100, collecting multi-omics data of blood brain barrier related cells to form an original set; s200, preprocessing the data and standardizing the data; s300, constructing a molecular network through cross-omics analysis, and screening key targets; s400, integrating target spot information to establish a structured target pool; s500, molecular docking and primary cell verification are carried out, and compounds capable of effectively regulating and controlling the permeability of the blood brain barrier are screened out. Through multi-omics integration and cross-omics analysis, a gene-protein-metabolite network is constructed, key targets of the blood brain barrier are accurately recognized, and a high-credibility target pool is provided; molecular docking and primary cell mixed culture verification are combined, efficient screening and functional safety evaluation of candidate compounds are achieved, the research and development cost is remarkably reduced, and an efficient technical path is provided for drug research and development.

The invention discloses a hyperlipemia tendency identification device and algorithm based on hand image features, palm center humidity and basic information of a patient. The method comprises the specific steps that a high-definition camera of the traditional Chinese medicine hand diagnosis instrument collects hand images of a plurality of detected persons, and a temperature and humidity sensor measures the palm center humidity; the method comprises the following steps: firstly, segmenting a hand image into eight anatomical areas such as a big thenar, a small thenar, fingers, a finger pulp and a hand back by adopting a U-Net model; identifying and classifying the features of each region by using a YOLOv8 model, and screening 11 key features from the 32 features; and then image features, palm center humidity data and basic information of a patient are fused and input into an integrated machine learning model of an AutoGluon framework, a prediction result of the tendency of the hyperlipemia is output, high, medium and low risk level evaluation is generated, and finally the prediction result of the tendency of the hyperlipemia is output. According to the method, the accuracy rate of a test set can reach 89% or above, and the method is suitable for scenes such as family health monitoring, community medical screening and hospital auxiliary diagnosis.