646 results about "Medical testing" patented technology

The invention relates to the field of medical examination data, and discloses a medical examination data sharing method based on cloud authentication, and the method comprises the following steps: carrying out the dynamic desensitization of original medical examination data at an edge node, and generating desensitization data meeting the privacy-utility balance; verifying the identity and authority of a request end user through a zero-knowledge proof protocol, and generating an authentication result bound with the privacy policy; performing hierarchical encryption on the desensitized data based on an anti-quantum attribute-based encryption algorithm to generate a ciphertext dynamically associated with the access attribute; and dynamically decrypting the data according to the real-time context parameters, and performing secondary desensitization processing in combination with an access scene. The technical scheme is optimized by adopting the dynamic desensitization and rate distortion theory, the technical effect of privacy-utility dynamic balance is achieved, and compared with the problems of fixed static desensitization rule and over-protection or under-protection in the prior art, the core defect that the method cannot adapt to the multi-scene data sharing requirement is overcome.

The invention discloses a health risk assessment method and early warning system based on multi-source data analysis. The health risk assessment method comprises the following steps: S1, collecting and preprocessing multi-source health data through medical detection equipment; s2, extracting key health indexes, sequence features and statistical features based on the health data set; s3, adopting a recurrent neural network model to construct a health risk assessment model; s4, optimizing structural parameters of the health risk assessment model by adopting an improved dragonfly algorithm; s5, performing performance evaluation on the health risk evaluation model by using the optimal parameter set; s6, deploying the final health risk assessment model in a health risk assessment and early warning system; and S7, when the health risk assessment result exceeds a preset risk threshold, automatically generating early warning information. According to the method, the recurrent neural network model, the improved dragonfly algorithm and the multi-source health data fusion optimization technology are combined, and health risk assessment and early warning based on multi-source data analysis are realized.

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 discloses a traditional Chinese medicine intelligent diagnosis and treatment and health management system based on big data, and relates to the technical field of traditional Chinese medicine informatization, and the system comprises a multi-source data collection and integration unit, a big data analysis and mining unit, and an intelligent diagnosis and treatment and health management service unit. The built-in functions of the multi-source data acquisition and integration unit comprise data sources and data integration, the data sources comprise clinical medical record data, health monitoring data, ancient medical registration literature data and modern medical examination data, and the data integration comprises data cleaning, data standardization and data fusion; the built-in functions of the big data analysis and mining unit comprise disease and syndrome type correlation analysis, prescription curative effect evaluation and optimization, personalized health management analysis and medicine research and development auxiliary analysis, and the operation steps of the disease and syndrome type correlation analysis comprise feature extraction, machine learning modeling and model evaluation and optimization.

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 discloses an examination result evaluation system in the technical field of medical examination evaluation. The system comprises a physiological dynamic recognition module, a critical state interpretation module, a process efficiency optimization module, a health trend prediction module, an examination accuracy improvement module, a result interpretation optimization module, a potential pathology mining module and a health evaluation comprehensive module. According to the method, the depth and the breadth of medical examination and evaluation are remarkably improved by introducing technologies such as a nonlinear dynamic model, fuzzy logic and a machine learning algorithm. Firstly, the application of the physiological dynamic recognition module enables the analysis of time sequence data to be more accurate, and subtle changes of physiological behaviors can be revealed, so that the capability of early recognition of diseases is improved. The introduction of the fuzzy logic shows higher flexibility and accuracy in the aspects of uncertainty and fuzziness of processing test results, and particularly provides finer support for medical decision making in the aspect of judgment of boundary values and critical states.

The invention relates to the technical field of medical examination, in particular to a method for calculating the definition of a leukocyte microscopic image based on deep learning, which comprises the following steps: preparing and expanding a data set of the microscopic leukocyte image, outputting a clear image and a blurred image, and enabling each image to have a corresponding definition evaluation index; performing multi-feature fusion definition evaluation on the microscopic leukocyte image based on comprehensive evaluation calculation of a Sobel operator, a Laplacian operator and information entropy; accessing multi-feature fusion definition evaluation into a deep learning model, and building a definition evaluation model; the definition evaluation model is trained, and in the training process, parameters of the definition evaluation model are adjusted by optimizing a loss function; the trained definition evaluation model is deployed in an automatic microscope system, and the problems that definition evaluation is carried out on the whole view, the definition evaluation algorithm is limited, and cell nucleus and cytoplasm characteristics are not distinguished in the prior art are solved.

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.

The utility model discloses a sampling device for medical examination, which comprises a sampler, a placing base for placing the sampler and a sampling rubber tube arranged at one end of the sampler, the inner wall of the sampler is in sliding connection with a piston, the top of the piston is fixedly connected with a pressing rod penetrating through the top of the sampler, and the top of the pressing rod is provided with a pressing plate. The outer side of the pressing rod is sleeved with a spring, one end of the spring is fixedly connected with the top of the piston, the other end of the spring is fixedly connected with the top of the sampler, the bottom of the sampler is in threaded connection with a connecting sleeve, a connector is arranged at one end of the connecting sleeve, a convex ring is integrally formed on the outer surface of one end of the connector, and a sampling rubber pipe is clamped to one end of the connecting sleeve. According to the utility model, the sampling rubber tube can be stably connected, no leakage in a sample transmission process is ensured, the risk of sample pollution is greatly reduced, cleaning and disinfection are not needed after single sampling, the time and labor cost of a disinfection link are reduced, and the inspection efficiency 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 relates to the technical field of automatic medical detection, in particular to an automatic blood coagulation detection system which comprises a sample state regulation and control module, a light source balanced imaging module, a dynamic image extraction module, a reaction process quantification module and a risk trend identification module. According to the invention, through interval mapping of the sample concentration degree and the specific gravity value, dynamic parameters are screened in combination with temperature and pH feedback, precise regulation and control of sedimentation and component states are realized, the imaging stability is improved, a light source illumination angle and power are dynamically matched according to intensity distribution and boundary overlap ratio, and the brightness consistency is enhanced; in image acquisition, brightness and boundary offset are synchronously analyzed, a consistent region is extracted, image continuity and quantization precision are improved, a reaction trend is superposed based on a section sequence, time sequence judgment accuracy is enhanced, stable mapping is formed by combining track and sample feature classification, the anomaly recognition capability is improved, and a closed-loop detection process is constructed. And the detection stability and individualized adaptability are enhanced.

The invention relates to the technical field of medical examination, in particular to a sectional urine sampling device applicable to medical examination, which comprises a urine sampling module, the urine taking module is divided into a urine dividing mechanism, a flow dividing mechanism, a sampling mechanism and a processing mechanism which are sequentially distributed from top to bottom, an operation panel is installed at the top of the urine dividing mechanism, the outer side of the urine dividing mechanism is communicated with a disinfection pipe, the other side of the disinfection pipe extends into the disinfection box to be communicated with a pump body, and the pump body is arranged in the disinfection box containing disinfectant; the outer side of the urine distribution mechanism is also fixedly connected with a slow air suction mechanism for exhausting air and a horizontally arranged hanging frame; the whole section of urine can be completely collected through the arranged urine taking module, the whole section of urine can be automatically divided into the front section of urine, the middle section of urine and the rear section of urine when the urine is discharged into the urine dividing mechanism, then the urine in the optimal time period is selected according to the actual situation, and it is ensured that detection data are accurate.

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 utility model discloses a sample collector for medical examination, which relates to the technical field of medical examination and comprises a lower tube body, an upper tube body inserted into the lower tube body and a sampling component arranged in the upper tube body. The lower pipe body is a hollow pipe body with an opening in the upper portion, the upper pipe body is a hollow pipe body which is arranged in a vertically-through mode, a conical puncturing end is arranged at the end, inserted into the lower pipe body, of the upper pipe body, and a sealing film is arranged at the position, located on the lower portion of the conical puncturing end in the initial state, of the lower pipe body. A sample treatment liquid is packaged between the sealing film and the end part of the lower tube body; according to the utility model, through the matching design of the sealing film and the conical puncturing end, the sample treatment liquid is in a completely sealed state before collection, the puncturing operation is realized through the linear movement of the upper tube body, no extra tool is needed, and the operation is convenient; the first limiting ring and the second limiting ring are matched with the detachable supporting assembly, the fixed distance between the upper pipe body and the lower pipe body is kept in the initial state, and it is ensured that the structure is stable during sampling.

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 provides a folic acid quality control product prepared by using an alternative matrix, and belongs to the technical field of medical detection. The folic acid quality control product is prepared from 5-methyltetrahydrofolic acid, 5, 10-methylenetetrahydrofolic acid and a substitute matrix, the alternative matrix comprises bovine hemoglobin, L-ascorbic acid and a glycine-hydrochloric acid buffer solution (pH 3.0). The alternative matrix can meet the matrix effect requirement and can stabilize the 5-methyltetrahydrofolic acid and the 5, 10-methylenetetrahydrofolic acid for a long time, and the matrix components can be obtained from commercial ways and are low in cost, so that the folic acid quality control product provided by the invention can be widely applied to production and use of folic acid detection reagents or kits, and has wide application prospects. The folic acid detection kit has important significance on market popularization and application of the folic acid detection kit.

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 relates to the technical field of image recognition, in particular to a medical examination information recognition method and system based on AI, and the method comprises the steps: collecting DICOM transmission counting, screening a density deviation path, selecting a highest value path for locking as a main use, calculating the feature cosine similarity through effective nodes of the main use path, and selecting a disease code with the highest similarity to generate a pathological classification result. According to the method, medical examination efficiency is optimized through dynamic path adjustment and multi-modal verification, DICOM transmission identification abnormal paths are monitored in real time, path distribution prevention delay is optimized in combination with parameters such as loads, hop counts and success rates, meanwhile, data consistency is verified through Hash chain type comparison, multi-dimensional features are extracted to be matched with a standard pathological library in a cosine similarity mode, and therefore the accuracy of medical examination is improved. According to the method, real-time resource scheduling and cross-level data verification are fused, feature cross verification is embedded, noise interference is reduced, and processing stability and pathological classification precision in a high-concurrency scene are improved.

The invention relates to a container control device of a medical detection analyzer. The container control device comprises a clamping piece and a control piece, wherein the clamping piece comprises an elastic clamping part for clamping a container; the ejection part is arranged in the clamping part in a sliding manner; the biasing piece is configured to be used for applying force to the ejection piece so that the ejection piece can push the container out of the elastic clamping part; the locking mechanism is configured in the mode that when the container is clamped in place by the elastic clamping part, the locking mechanism enables the ejection piece to be in a standby state in which the force applied by the bias piece cannot be transmitted to the container; and the unlocking mechanism is configured to be used for releasing the standby state of the ejection piece so as to push the container out of the clamping piece under the action of the bias piece. In addition, the invention further provides a medical detection analyzer comprising the container control device. According to the container control device and the medical detection analyzer, the structure can be simplified, the cost can be reduced, and the reliability and the stability can be improved.

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 utility model relates to the technical field of oscillation devices, and discloses a clinical medical examination oscillation device which comprises a base and an oscillation mechanism arranged at the upper end of the base, a placing structure is further arranged at the upper end of the base, a test tube body is arranged on the surface of the placing structure, and a tube plug is arranged at an opening of the test tube body. A limiting frame is fixedly installed at the upper end of the base, test tube bodies are inserted into inserting holes, then a motor is started, a rotary disc can be driven to rotate, a containing frame can be pushed to reciprocate under driving of a connecting rod and a hinge base, the containing frame can be limited through a limiting groove and a limiting block, and oscillation of the test tube bodies is achieved; a reagent in the test tube body can be prevented from spilling out under the action of the tube plug, the auxiliary frame can be pulled upwards, the supporting rod can slide in the placement groove and is fixed by using a bolt, the overall height of the placement frame and the auxiliary frame can be adjusted, the placement frame can adapt to the test tube bodies with different sizes, and the use flexibility is improved.

The invention discloses a smear device for clinical medical examination, and belongs to the technical field of smears for clinical medical examination, the smear device for clinical medical examination comprises an examination table and a support frame fixed on the examination table, a glass slide is fixedly mounted on the support frame, a glass slide is mounted in the glass slide in an embedded manner, and the glass slide is fixed on the examination table. An electric sliding rail assembly is fixedly installed on the inspection table, the sliding end of the electric sliding rail assembly is connected with a movable frame, the movable frame is longitudinally and slidably sleeved with a lifting frame, a steering support is rotationally installed on the lifting frame, and a pushing piece is fixedly installed in the steering support through a bolt. An inspection mechanism for movably shooting smear uniformity is arranged on the inspection table, and a speed limiting mechanism for limiting the smear speed and keeping the smear uniformity is further arranged on the inspection table; in the smear process, the smear and camera monitoring are kept consistent, the smear speed can be adjusted in time according to the uniformity of the monitored smear, and the quality of the prepared smear is improved.

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 discloses a medical examination index reduction method based on rough set positive domain and information entropy synthesis, is suitable for high-dimensional data attribute reduction and knowledge discovery in scenes such as medical data analysis, and provides a new reduction strategy by fusing two perspectives of a rough set theory and an information theory method. The comprehensive importance degree of the attributes is obtained through a weighted average mode, and the weight is determined by the ratio of the positive domain to the boundary domain. Iterative reduction is carried out according to the comprehensive importance, deterministic and non-deterministic elements are reasonably considered, the problem of feasibility of attribute reduction of a large-scale fuzzy information decision system is solved, and a more accurate reduction set is obtained. Key diagnosis indexes are conveniently focused, the diagnosis efficiency and accuracy are improved, the clinical interpretability is enhanced, unnecessary detection items are reduced, and the effects of optimizing data, improving the diagnosis efficiency and saving the medical cost are achieved.