479 results about "Medical testing" patented technology

The invention provides a medical examination data analysis system and method based on artificial intelligence. The method comprises the steps of obtaining a time sequence data matrix of multiple examination indexes of a target patient at different time nodes through medical examination data of the target patient; labeling pathological labels of various examination indexes in the medical examination data, and determining medical semantic association features among different examination indexes of the target patient through the pathological labels; according to the medical semantic association features and the time sequence data matrix, determining a time sequence association relationship of different inspection indexes of the target patient on a pathological level, and generating a fusion feature vector of the health state of the target patient according to the time sequence association relationship; and an abnormal evolution feature of the current health state of the target patient is obtained by combining an abnormal detection model with the fusion feature vector, and then an auxiliary analysis result of the pathological risk of the target patient is output to medical personnel. By adopting the scheme of the invention, the dynamic change trend analysis of the disease course risk state of the patient can be realized based on the medical semantic perception ability.

The invention belongs to the technical field of data processing, and discloses a construction method and system based on a medical examination medical knowledge base and a medium. Comprising the steps that a basic medical data set is collected, data cleaning is conducted, and a structured medical data set is output; constructing a multistage medical dictionary and establishing semantic mapping with the structured medical data set to generate a standard medical data set; carrying out medical related entity extraction on the standard medical data set and establishing a semantic relationship of each medical entity to obtain a medical entity set; performing semantic alignment on the medical entity set to obtain a semantic alignment entity set; constructing a medical examination knowledge rule base and constructing an initial medical examination knowledge graph in combination with the semantic alignment entity set; performing entity association extension on the initial medical examination knowledge graph, and outputting an enhanced medical examination knowledge graph; real-time clinical data are collected, and the medical examination knowledge graph is updated and enhanced based on the real-time clinical data to obtain the medical examination knowledge base, so that convenience is provided for medical decision making and intelligent reasoning diagnosis.

The invention relates to the technical field of medical detection, in particular to a sacroiliac arthritis judgment method and system based on X-rays, and the method comprises the steps of multi-modal data synchronous collection, image data real-time optimization and control, cross-modal causal reasoning and three-dimensional reconstruction, and AI-based lesion preliminary analysis and dynamic grading and interpretability report generation. According to the method, a real-time image processing technology is integrated in a data acquisition stage, an original image is directly and dynamically optimized at an imaging end, and the image resolution and the detail definition are improved through an advanced enhancement algorithm; the problems of delay and detail loss caused by relying on post-processing in a traditional method are solved, so that a doctor can obtain a high-quality diagnosis image in real time; by means of the optimization, the requirement for repeated shooting is reduced, and the availability and diagnosis efficiency of images are remarkably improved.

The invention relates to the related technical field of clinical data analysis, in particular to a clinical medical examination data classification system and method based on big data analysis, a man-machine interaction module is used for extracting and displaying a data classification result of a user, providing a Web / mobile terminal interface and supporting examination data uploading, classification result visualization and report exporting; the data processing module is used for realizing data cleaning (denoising and missing value filling), standardization (LOINC coding mapping) and feature extraction; the intelligent classification module integrates a random forest and an SVM algorithm model and supports automatic classification of inspection items; the database module is used for storing user information, clinical medical examination data of the user, historical clinical medical examination data, a clinical medical examination knowledge graph, clinical medical examination keywords, model metadata and a data classification result; the intelligent classification system for clinical medical examination data can significantly improve medical efficiency and decision quality through standardized integration and AI analysis.

The invention provides an oscillation device for clinical medical examination, and relates to the field of medical equipment. The oscillation device for clinical medical examination comprises a barrel, a concave groove is formed in the inner wall of the barrel, a second rotating disc is rotationally connected into the concave groove, an upper fixing sleeve is fixedly connected to the middle of the bottom end of the second rotating disc, and a lower connecting block is fixedly connected into the upper fixing sleeve. A first rotating disc is fixedly connected to the bottom end of the lower connecting block, a turbine is fixedly connected to the outer side of the bottom end of the first rotating disc, a worm is meshed with one side of the turbine, and a first motor is fixedly connected to one side of the bottom end in the barrel. The two ends of the rotating rod are rotationally matched, so that the rotating rod can be pulled and pushed to shake the rotating column, the rotating column is rotationally connected with the top plate, an oscillator at the top end of the rotating column can be shaken, the vibration effect is completed through the structure, and the vibration effect is improved.

This invention relates to the field of medical testing, specifically to a set of biomarkers, reagent kits, and their applications for diagnosing hypertension in children. This invention involves collecting tongue / intestinal samples from obese children with hypertension, obese children, and healthy individuals, performing metagenomic sequencing, and statistically analyzing the sequencing data using bioinformatics to identify disease-related tongue / intestinal flora. By integrating tongue / intestinal flora with disease information, a combination of flora biomarkers is obtained. A binary classification prediction model constructed using this combination can maximally detect hypertension in obese children.

The invention discloses a case misdiagnosis identification method and device and a storage medium, relates to the technical field of medical technology and machine learning, and discloses the steps that multi-source heterogeneous medical detection data of a to-be-identified case and a disease diagnosis result and a treatment strategy of a doctor on the to-be-identified case are acquired; based on the multi-source heterogeneous medical detection data, the disease diagnosis result and the treatment strategy, diagnosis and treatment path matching is conducted on a pre-constructed typical disease knowledge base, the corresponding diagnosis and treatment path deviation degree is obtained, and the typical disease knowledge base comprises multiple disease entries and reference diagnosis and treatment paths corresponding to the disease entries; and inputting the multi-source heterogeneous medical detection data, the disease diagnosis result, the treatment strategy and the diagnosis and treatment path deviation degree into a misdiagnosis recognition model, and performing misdiagnosis recognition on the to-be-recognized case based on the misdiagnosis recognition model to obtain a corresponding misdiagnosis recognition result, thereby solving the technical problem of low misdiagnosis recognition accuracy of the actual diagnosis and treatment path of the case in the prior art, and improving the accuracy of the misdiagnosis recognition. And the misdiagnosis identification accuracy is improved.

The invention belongs to the field of medical examination equipment, and provides a medical examination sampling device and a use method.The medical examination sampling device comprises a sampling table, a fixed baffle is fixedly installed on the edge of the upper surface of the sampling table, an operation window is formed in the bottom of one end of the fixed baffle, and a fixed groove is formed in the middle of the top end of the sampling table; the conveying mechanism comprises supporting rollers, the supporting rollers are symmetrically and rotationally installed on the two side edges of the inner wall of the fixing groove, the outer surfaces of the supporting rollers are sleeved with a conveying belt, a stepping motor is installed in the middle of one end of each supporting roller, positioning assemblies are arranged on the outer surface of the conveying belt at certain intervals, and limiting clamping pipes are installed on the portions, in the positioning assemblies, of the outer surface of the conveying belt. By means of the automatic separating and collecting structure (the connecting rotary disc, the fixing clamping sleeve and the collecting box), non-contact recycling of blood sampling parts is achieved, direct contact between medical workers and blood samples and sharp tools is reduced, and occupational exposure risks are remarkably reduced.

The invention discloses a group of pyemia specific biomarkers and application thereof, and belongs to the field of medical detection.The biomarkers are formed by combination of alpha 1-microglobulin / Bikunin precursor protein and one or more of antithrombin III protein, apolipoprotein A1 or apolipoprotein H, according to the invention, seven core proteins, namely APOA1, APOH, AMBP, SERPINC1, F2, FGG and FGB, are screened from TMT proteomics of serum of a clinical hemorrhagic patient, and four more important proteins, namely APOA1, APOH, AMBP, SERPINC1, F2, FGG and FGB, are obtained by further screening the seven proteins in a hemorrhagic cell model and the clinical hemorrhagic patient. The four proteins are verified again in serum of a hemorrhagic mouse animal experiment and an expanded-scale clinical hemorrhagic patient, and the potential of the four core proteins as serum biomarkers for early diagnosis of hemorrhagic disease is determined.

The invention discloses an intelligent respiratory disease detection system based on lung function measurement indexes, and relates to the technical field of intelligent medical detection. The problems that diagnosis standards are not uniform and depend on experience, primary doctors are prone to missed diagnosis or misdiagnosis due to insufficient experience, and the efficiency of the detection process is low are solved. According to the method, a machine learning model is constructed based on lung function indexes, parameters are optimized through five-fold cross validation, automatic classification of asthma, COPD and ILD / DPLD is achieved, the overall diagnosis accuracy rate reaches 81.3%, the limitation that traditional diagnosis depends on doctor experience is broken through, and the basic medical diagnosis capacity is especially improved. Healthy people are rapidly eliminated through the FVC / FEV1 ratio, invalid calculation is reduced, meanwhile, multi-model weighted fusion is adopted for complex cases, diagnosis robustness is improved, it is ensured that diagnosis results conform to medical logic, the recognition degree of doctors is enhanced, a data basis is provided for clinical research and curative effect tracking, and respiratory disease diagnosis is promoted to develop towards the direction of automation and precision.

The invention provides a deployment method, device and system for a specific detection model in a medical scene, is used for carrying out localized deployment on a mature medical examination model in a hospital, specifically combines a container deployment technology and a container arrangement technology, provides corresponding model calling services for medical personnel more conveniently, efficiently and safely, and improves the medical examination efficiency. Dual requirements of data security compliance and model real-time calling can be effectively balanced, a safe, extensible and high-reliability operation platform is provided for actual landing of a digital algorithm, external dependence is greatly reduced, and the real-time performance of the digital algorithm is improved. The method provides possibility for rapid verification and iterative algorithm of hospital informatization departments and researchers in a clinical environment, achieves intelligent medical assistance of closed-loop, safe, controllable and efficient optimization in a hospital, has large-scale popularization value, and provides robust AI technical support for various clinical diagnosis, inspection analysis and scientific research work.

The invention relates to the technical field of blood collection, in particular to a blood collection device for medical examination, which comprises a blood collection tube preprocessing module, a tourniquet binding module arranged above a placement platform and used for carrying out tourniquet on a patient and a vein recognition and positioning module used for recognizing and positioning veins of the patient, a circulating rotation disinfection module used for being in contact with the arm of the patient is further arranged in the placement platform; the tourniquet is tightened through the tourniquet retracting and releasing device, the pressure sensor can detect the compression force on the arm of a patient, automatic adjustment is achieved, manual binding is not needed, too loose and too tight conditions are not prone to occurring, the binding quality is ensured, the vein recognition and positioning module can recognize the vein position below the arm epidermis, infrared positioning is adopted, and the positioning accuracy is improved. The blood collection tube pretreatment module can automatically shake a vacuum collection tube after blood drawing is completed, it is ensured that an anticoagulant is mixed with a blood sample, and the blood sample quality is ensured.

The invention discloses a laser Doppler heterodyne noninvasive blood glucose concentration measuring device and method, and belongs to the technical field of medical detection. Comprising a laser generating module which comprises a laser, and a first 1 / 2 wave plate and a polarization splitting prism which are sequentially connected with the laser; and the interference light path module is connected to the two sides of the polarization splitting prism respectively and comprises a first optical fiber coupler connected with the polarization splitting prism, and a second 1 / 2 wave plate and a second optical fiber coupler which are sequentially connected with the other side of the polarization splitting prism. The device has the advantages that noninvasive detection can be achieved, blood sampling wounds are avoided, and the comfort level of a patient is improved; the measurement precision is high, and the blood glucose value can be quickly and accurately obtained by using heterodyne interference and frequency shift technologies.

The invention discloses a Wright staining peripheral blood cell accurate identification system and method based on intelligent microscopic imaging and multi-modal fusion deep learning, belongs to the crossing field of medical examination and artificial intelligence, and is suitable for cell morphology analysis under a 10 * 40-time microscope. The core scheme comprises the following steps: standardized slide preparation and dyeing (the slide pushing angle is 25 + / -2 degrees, the pH is 6.8 + / -0.2, and color sensing dynamic regulation is performed); intelligent imaging (focusing formula and color normalization; the method comprises the following steps of (1) data processing, (2) data processing, (3) data processing, (4) data processing, (5) data processing, (6) data processing, (7) data processing, (8) data processing, (7) data processing, (8) data processing, (8) data processing, (8) data processing, (8) data processing, (8) data processing and (8) data processing.

The invention provides an image-text medical examination report generation method and system based on deep learning, and the method comprises the steps: carrying out the structural integration of an original examination record generated in a medical examination process and a medical image sequence, and obtaining an examination data unit set containing a time sequence incidence relation, constructing a feature mapping rule base based on clinical diagnosis decision logic, and converting quantitative indexes and qualitative description in the test data unit set into standardized clinical feature representation through rule matching; calling a deep generation model to carry out adaptive generation processing on the standardized clinical feature representation, adjusting a text generation strategy according to the diagnosis association strength between the features, and generating a medical description text conforming to the clinical narrative logic; and performing diagnosis focus association typesetting on the medical description text and the corresponding medical image sequence, establishing a bidirectional reference relationship between the text description and the image feature region through semantic anchoring, and generating an image-text medical examination report. According to the invention, the report generation efficiency and quality are improved.

The present invention discloses a medical test index simplification method based on the combination of rough set positive domain and information entropy, which is suitable for high-dimensional data attribute simplification and knowledge discovery in scenarios such as medical data analysis. By integrating the two perspectives of rough set theory and information theory methods, a new simplification strategy is proposed, which obtains the comprehensive importance of attributes by weighted average, and its weight is determined by the ratio of the positive domain to the boundary domain. It performs iterative simplification according to the comprehensive importance, reasonably takes into account the deterministic and non-deterministic elements, solves the feasibility problem of attribute simplification in large-scale fuzzy information decision-making systems, and obtains a more accurate simplified set. It is convenient to focus on key diagnostic indicators, improve diagnostic efficiency and accuracy, enhance clinical interpretability, reduce unnecessary test items, and play a role in optimizing data, improving diagnostic efficiency, and saving medical costs.

The invention discloses a microbial culture device for medical examination, which comprises a cylinder body, a storage cavity is arranged at the upper end of the cylinder body, a cover body is arranged in the storage cavity, a through hole is formed in the cover body, a sealing cover is arranged at the through hole, a support frame and a lifting mechanism are arranged in the storage cavity, the support frame is used for placing a culture dish, and the lifting mechanism can push the culture dish out of the through hole. A liquid heating assembly is arranged at the bottom of the barrel, a first water channel is formed in the side wall of the storage cavity, a second water channel is formed in the cover, the liquid heating assembly communicates with one end of the first water channel, the other end of the first water channel communicates with one end of the second water channel, and the other end of the second water channel communicates with the heating assembly. The supporting frame, the lifting mechanism and the liquid heating assembly are all electrically connected to the control panel. The culture dishes on the supporting section frames extend out of the through holes with smaller openings through the lifting mechanisms, so that the heat loss can be reduced under the condition of water bath heating, and the temperature balance is ensured.

The invention belongs to the technical field of medical detection, and particularly relates to a marker for smoke disease diagnosis and application thereof. The invention discloses a marker for smoke disease diagnosis. The marker for smoke disease diagnosis is miRNA (micro Ribonucleic Acid); the miRNA is hsa-miR-4433a-5p, and the nucleotide sequence of the miRNA is as shown in SEQ ID NO. 1 (sequence identifier number 1). Experiments prove that the expression level of hsa-miR-4433a-5p in smoke disease patients is obviously higher than that of hsa-miR-4433a-5p in healthy people, and hsa-miR-4433a-5p can be used as a marker for smoke disease diagnosis. Meanwhile, the marker for smoke disease diagnosis is applied to preparation of the kit, the content of hsa-miR-4433a-5p in serum can be detected through a real-time fluorescent quantitative PCR technology, and the kit has the advantages of being high in sensitivity and accuracy and wide in application prospect.

The application discloses a clinical medical examination knowledge base construction and application method, device, equipment and medium, relates to the computer technical field, and includes: converting the collected clinical medical data into corresponding dense vectors based on a preset large language model to obtain a target clinical medical examination knowledge base; performing a configuration operation of a dialogue retrieval mode on the target clinical medical examination knowledge base, and after the configuration is completed, performing vector conversion on a received natural language sentence to be replied based on the preset large language model to obtain a corresponding question vector; by calculating the cosine similarity between the question vector and each dense vector in the target clinical medical examination knowledge base, the most relevant target vector to the question vector is determined; and based on the preset large language model and the target vector, a corresponding target natural language reply sentence is generated to reply to the natural language sentence to be replied. In this way, the retrieval efficiency can be effectively improved, and the convenience of retrieval is further improved.

The invention relates to the technical field of medical systems, in particular to an intelligent diagnosis auxiliary system based on informatization planning, which comprehensively collects inspection operation parameters and patient physique information and covers data in multiple aspects from inspection process details to patient individual physique characteristics. The data are mapped to a test method-interference factor relation network through a knowledge graph, the influence of test operation interference and patient physique interference on diagnosis can be comprehensively analyzed, the influence condition of interference parameters is quantified by adopting a natural constant power formula in test process anomaly analysis and physique-to-diagnosis disease anomaly influence analysis, and the diagnosis accuracy is improved. The non-linear quantification mode better accords with the actual relation between interference and influence in a medical examination operation scene, the influence degree of the examination process and the patient physique on diagnosis can be more accurately evaluated, and then a more reliable basis is provided for diagnosis.

The invention discloses a physical examination report interpretation method and device based on knowledge distillation. The method relates to the technical field of artificial intelligence, and comprises the following steps: obtaining a to-be-interpreted target physical examination report from a target queue; performing standardization processing on data in the target physical examination report through a classification model in a first container instance to obtain a medical examination data set with examination items as categories; performing abnormal index identification on the medical examination data set to obtain abnormal index data, and processing the medical examination data set through a medical entity identification model in a second container instance to obtain a medical entity set, and processing the medical entity set and the abnormal index data through an interpretation model in a third container instance to obtain an interpretation result. According to the method and the device, the problem of relatively low efficiency of interpreting the physical examination report due to the fact that the physical examination report is interpreted depending on manual professional knowledge in related technologies is solved.

The utility model discloses a sampling device for medical examination, which comprises a sampling tube, the two sides of the top of the sampling tube are fixedly connected with mounting plates, a piston rod is arranged in the sampling tube, the bottom end of the piston rod is fixedly connected with a piston, the top end of the piston rod is fixedly connected with a drawing plate, and the drawing plate is fixedly connected with the sampling tube. Baffles are fixedly connected to the two sides of the drawing plate, a mounting groove is fixedly connected to the top of the mounting plate, positioning holes are formed in the two sides of the mounting groove, a U-shaped plate is movably connected to the interior of the mounting groove, a sliding groove is formed in the inner wall of the U-shaped plate, and a limiting rod is fixedly connected to the inner wall of the sliding groove. The outer wall of a limiting rod is slidably connected with a quantitative plate, the quantitative plate can block baffles on the two sides of a drawing plate when the device is used for sampling, the drawing plate is prevented from continuously drawing upwards, accordingly, movement of a piston is prevented, quantitative sampling of samples is achieved, and the height of the quantitative plate can be adjusted by rotating a screw rod. And quantitative collection work of different doses can be realized.

The utility model belongs to the technical field of medical examination experiment instruments, and particularly relates to a test tube oscillator. Aiming at the problem that the existing test tube oscillator is tedious to fix and adjust, the oscillator provided by the utility model comprises an oscillator main body, an oscillation disc, a sliding rod, a pressing plate, a first elastic piece and a locking assembly, the oscillation disc is connected with the output end of the oscillator body, the two sliding rods are arranged on the two sides of the oscillation disc at the upper end of the oscillator body and provided with lock holes, the pressing plate and the locking assembly are longitudinally and slidably connected with the sliding rods, the first elastic piece is fixedly connected between the pressing plate and the locking assembly, and the locking assembly can be locked with the lock holes. When the test tube is fixed, through simple operations such as unlocking, lifting and pressing, the test tube is fixed by utilizing pressure generated by compression of the first elastic piece. The test tube fixing device is convenient to operate, high in error-tolerant rate and capable of quickly fixing test tubes with different heights; fixation is stable and reliable, and test tube loosening is avoided; the application range is wide, diversified requirements of medical examination can be met, and medical examination efficiency and result accuracy are effectively improved.

The utility model discloses a cell centrifuge for medical detection, which comprises a cell centrifuge body, a centrifuge body, a fixed hood, a test tube and an arc-shaped splint, the centrifuge body is arranged inside the cell centrifuge body, and the edge position inside the centrifuge body is provided with centrifugal grooves at equal intervals; the test tube is arranged in the centrifugal groove, the motor is mounted at the bottom of the cell centrifuge body below the centrifuge body, the output end of the motor is fixedly connected with the centrifuge body, the fixed hood is mounted at the center of the top end of the centrifuge body, and the bracket is mounted at the bottom of the fixed hood; a rotating disc is rotatably installed in the rotating handle above the support, arc-shaped through grooves are formed in the rotating disc at equal intervals, push rods are slidably installed in the support, and the arc-shaped clamping plates are fixed to one ends of the push rods. The test tube rack has a fixing function, is convenient for fixing test tubes, and prevents the test tubes from shaking and falling off.

1. Name of the product in this design: Medical Detection Data Acquisition Device. 2. Purpose of this design: For collecting medical test samples. 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 discloses a method for measuring the pressure in the heart cavity of a mouse, and relates to the technical field of experimental animal medical detection, and the method comprises the following steps: cutting an incision of about 1cm in the neck of the mouse; placing two sutures below the common carotid artery, and ligating the common carotid artery by using the suture at the distal end; the other section of suture line is placed in the middle of the right common carotid artery, the carotid artery is lifted up, the blood filling condition is observed, an opening is formed in the blood vessel, a pressure volume catheter is inserted, and meanwhile the suture line at the telecentric end is slightly pulled backwards to prevent bleeding; the pressure volume catheter is inserted into the left ventricle through the right common carotid artery, and the left ventricle pressure maximum rising rate and the left ventricle pressure maximum falling rate are collected. By means of the carotid artery approach, serious trauma caused by thoracotomy can be prevented, and the cardiac physiology can be possibly affected by the operation. Therefore, the carotid artery approach is more suitable for a long-time pressure collection experiment.

The utility model relates to the technical field of medical detection devices, and discloses a glycosylated hemoglobin detection device, which comprises a sampling mechanism, a detection mechanism and a control mechanism, the sampling mechanism comprises an injection pump set, a sampling needle and a sampling valve, the sampling valve is a six-way sampling valve, the injection pump set is connected with a first port of the sampling valve, and the sampling needle is connected with a second port of the sampling valve; the separation mechanism comprises an eluent group, a mixer and a chromatographic separator, the eluent group is connected with a fifth port of the sample injection valve, the chromatographic separator is connected with a sixth port of the sample injection valve, and two ends of the mixer are connected with a third port and a fourth port of the sample injection valve; the inspection mechanism comprises a filter and an inspector, the filter is arranged between the mixer and the chromatographic separator, and the inspector is connected with the chromatographic separator. According to the utility model, the glycosylated hemoglobin can be rapidly and accurately detected through an accurate sample introduction and separation mechanism, so that the detection efficiency is improved. The automation degree of the detection process is high, the requirement for manual operation is reduced, and the possibility of human errors is reduced.

This disclosure belongs to the field of medical testing technology, and specifically relates to a classification, diagnostic, and prediction method, system, and electronic device for congenital neurodevelopmental disorders. Addressing the clinical diagnostic challenges of congenital neurodevelopmental disorders, this disclosure establishes for the first time a classification, diagnostic, and prediction method for congenital neurodevelopmental disorders based on whole-genome methylation signatures and customized SVM machine learning. This method achieves one-stop differential diagnosis across multiple mechanisms and diseases, filling a gap in existing technologies and providing a novel and efficient solution for the accurate diagnosis of congenital neurodevelopmental disorders.