11 results about "Established diagnosis" patented technology

The invention provides a method for establishing a diagnosis and treatment system for digestive system disease multi-modal information. The method comprises the following steps: S1, collecting multi-modal information for labeling and preprocessing; s2, extracting a feature vector and embedding a label into the multi-modal information according to the labeled information; s3, splicing and mapping the feature vector and the tag to a unified dimension to obtain an enhanced feature vector; s4, fusing the enhanced feature vectors to form a multi-modal feature matrix, performing linear mapping and weighted aggregation on the multi-modal feature matrix to obtain global fusion vectors, and collecting to generate a fusion vector sequence; s5, enhancing the time sequence information of the global fusion vector sequence, enhancing the spatial information of the spatial relevance of the specific feature of the part, and performing interactive fusion to obtain a spatio-temporal joint feature; s6, performing classification prediction on the disease stage or the specific pathological type, and outputting a diagnosis result; and S7, performing semantic association on the diagnosis result and the medical knowledge graph, sharing data to an online health intelligent platform, and providing a personalized decision basis for clinicians.

The invention provides a disease image recognition system based on Shapley value guidance, and relates to the field of medical image processing. The method comprises the following steps: acquiring a first image through an image acquisition module, carrying out data preprocessing, inputting a second image into an established diagnosis model establishment module, carrying out classified diagnosis, feature extraction and RA classification on an X-ray film image by adopting a trained diagnosis model, carrying out Shapley value analysis and visualization processing on an RA classification result, and obtaining a diagnosis result of the X-ray film; and obtaining an image recognition result based on a result of the Shapley value analysis module in combination with the current clinical data. According to the method, image interference is reduced, data features are effectively extracted, the image recognition rate and accuracy are improved, and the transparency of the model is enhanced, so that the misdiagnosis rate and missed diagnosis rate are reduced, the accuracy and reliability of rheumatoid arthritis diagnosis are improved, the user experience is improved, and the working efficiency is improved.

To provide a diagnosis and a prescription support system: having a large-scale language model additionally learn patient records of a great amount of diagnosed cases; having the additionally learned large scale language model propose an effective inspection plan for determining diagnosis, from symptom remarks obtained from a visiting diagnosis undetermined patient; support obtaining an established diagnosis by integrating the obtained testing results; and furthermore propose a suitable treatment plan on the basis of the established analysis.SOLUTION: An electronic medical chart system also combined with a large scale language model includes: "possible diagnosis term, additional symptoms, body remarks, and test answer means" for responding to at least one of a possible diagnosis name and a list of the probability, recommended additional symptoms, body remarks, and a test; and sequential diagnosis improvement means repeating "symptoms, physical remarks, and test result data provision means" and "diagnosis name with a possibility, additional symptoms, body remarks, test answer means" until the list of the diagnosis name and its probability has sufficient accuracy as a definite diagnosis.SELECTED DRAWING: Figure 5

[Problem] To allow a large-scale language model to be additionally trained with patient records of a large number of diagnosed cases, to assist the additionally trained large-scale language model in proposing an efficient examination plan for establishing a diagnosis from symptom findings obtained from an undiagnosed patient visiting the clinic, and in obtaining an established diagnosis by integrating obtained examination results. [Solution] An electronic medical chart system in which a large-scale language model is used in combination is provided with: a "possible diagnosis name, additional symptom, body finding, and examination answering means" for answering at least one of a list of possible diagnosis names and probabilities thereof, a recommended additional symptom, a body finding, and examination; and a sequential diagnosis improving means for repeating the "symptom, body finding, and examination result data providing means" and the "possible diagnosis name, additional symptom, body finding, and examination answering means" until the list of possible diagnosis names and probabilities thereof has sufficient accuracy as an established diagnosis.

The invention discloses a marker combination and application thereof in diagnosis of expression metaplasia of spasmolysis polypeptide. The marker combination comprises an SCD1 marker combination, a PHB1 marker combination and a p-ERK marker combination. The marker combination is based on joint detection of SCD1, PHB1 and p-ERK markers, the sensitivity and the specificity of an established diagnosis model are remarkably superior to those of a traditional single detection method, and early recognition of the potential precancerous lesion SPEM is facilitated.

The invention relates to the technical field of molecular diagnosis and early screening of tumors, and particularly discloses a plasma circulating microbial marker for early screening of lung cancer and application of the plasma circulating microbial marker. The marker comprises the following components: staphylococcus aureus, fusobacterium nucleatum, klebsiella pneumoniae, alternaria simplex, legionella pneumophila, neisseria mucosa, Ralstonia petii, pasteurella multocida, and haemophilus parainfluenza (Haemophilus parainfluenza), and the marker comprises the following components: staphylococcus aureus, fusobacterium nucleatum, klebsiella pneumoniae, alternaria simplex, legionella pneumophila, neisseria mucosa, Ralstonia petii, pasteurella multocida, and Haemophilus parainfluenza (Haemophilus parainfluenza). According to the method, nine characteristic microbial markers are detected in combination with a low Pass WGS technology, a high-precision diagnosis model is constructed through a machine learning algorithm, the established diagnosis model has excellent stability and clinical applicability, efficient recognition of early lung cancer can be achieved, and the detection cost can be greatly reduced.

The present application relates to the field of medical informatization and artificial intelligence technology, and specifically provides a medical record connotation quality control method and device based on a large language model, which has the following steps: S1, medical record document data access, document content preprocessing; S2, clear quality control content, construct quality control rule library; S3, construct medical knowledge base: based on clinical guidelines and evidence-based medicine evidence base, establish diagnosis standard, drug, treatment project, inspection project knowledge base; S4, entity extraction: use a large language model to extract diagnosis, drug, treatment project and inspection project name; S5, model reasoning: query the relevant information of the extracted entity in the knowledge base, according to the quality control rules, combine the queried relevant information with the medical document and submit them to the large model for reasoning to give the quality control result; S6, problem collection, model optimization. Compared with the prior art, the present application can significantly improve the intelligent level of medical record connotation quality control, effectively assist clinical doctors and quality control personnel to improve the quality of medical record writing, ensure medical safety, and improve hospital management efficiency.

A method for the in vitro diagnosis of the risk of delayed cerebral ischemia (DCI) following subarachnoid hemorrhage from a ruptured aneurysm (aSAH) which includes the following steps: collection of a blood sample from the patient; quantitative determination of 8-iso-prostaglandin F2α (F2-IsoP) concentration in plasma; comparison of the concentration thereof in plasma with the reference value; collection of at least one further blood sample; quantitative determination of the concentration of endothelial nitric oxide synthase (eNOS) and / or nicotinamide adenine dinucleotide phosphate (NADPH) in plasma; comparison of the concentration thereof in plasma with the reference value; analysis of the obtained results and establishing diagnosis. A marker substance for the in vitro diagnosis of the risk of occurrence of DCI selected from 8-iso-prostaglandin F2α (F2-IsoP), endothelial nitric oxide synthase (eNOS), nicotinamide adenine dinucleotide phosphate (NADPH) and combinations thereof and the use thereof as a screening test for the in vitro diagnosis of DCI following aSAH.

The application relates to a flow meter calibration method, device, computer equipment and storage medium, which comprises the following steps: acquiring characteristic data of a target flow meter, wherein the characteristic data comprises acceleration and flow value of the target flow meter; determining whether the state of the target flow meter is abnormal according to the characteristic data; if the state of the target flow meter is abnormal, determining a diagnosis parameter of the target flow meter according to the characteristic data; and searching for an abnormal reason corresponding to the diagnosis parameter in a pre-established diagnosis database according to the diagnosis parameter, wherein the diagnosis database comprises a mapping relationship between diagnosis parameters and abnormal reasons of a template flow meter. The above method can monitor and record abnormal vibration data of the target flow meter in real time, and can diagnose the reason for the abnormal vibration of the target flow meter in a timely manner.

The invention discloses application of linoleic acid as a biomarker and a kit for detecting the biomarker, and belongs to the technical field of medical detection. According to the model, the biomarker content level serves as an input variable, a diagnosis model is constructed, the biomarker is linoleic acid, and the model use equation is as follows: score = 2.09 * linoleic acid content level / 1000-9.399. Among coronary heart disease groups, linoleic acid in patients with hyperlipemia is obviously higher than linoleic acid in non-hyperlipemia groups, the established diagnosis model has good sensitivity and specificity, and the provided kit can realize diagnosis and prognosis monitoring of hyperlipemia and can guide lipid nutrition intake of patients in the treatment process.

A method for the in vitro diagnosis of the risk of delayed cerebral ischemia (DCI) following subarachnoid hemorrhage from a ruptured aneurysm (aSAH) which includes the following steps: collection of a blood sample from the patient; quantitative determination of 8-iso-prostaglandin F2α (F2-IsoP) concentration in plasma; comparison of the concentration thereof in plasma with the reference value; collection of at least one further blood sample; quantitative determination of the concentration of endothelial nitric oxide synthase (eNOS) and / or nicotinamide adenine dinucleotide phosphate (NADPH) in plasma; comparison of the concentration thereof in plasma with the reference value; analysis of the obtained results and establishing diagnosis. A marker substance for the in vitro diagnosis of the risk of occurrence of DCI selected from 8-iso-prostaglandin F2α (F2-IsoP), endothelial nitric oxide synthase (eNOS), nicotinamide adenine dinucleotide phosphate (NADPH) and combinations thereof and the use thereof as a screening test for the in vitro diagnosis of DCI following aSAH.