13 results about "Medline database" patented technology

The invention relates to the field of medical information processing and traditional Chinese medicine curative effect evaluation, in particular to a diabetic nephropathy traditional Chinese medicine curative effect evaluation method based on patient report outcome. The method comprises the following steps: searching related symptoms and clinical characterization data of diabetic nephropathy through a medical database, extracting target entries, performing language standardization processing, constructing an initial candidate entry set, calculating the occurrence frequency of each symptom entry, and screening entries meeting a set threshold value to form an entry set; carrying out dimension division on the entry set according to feature attributes to form a preliminary dimension structure set; forming a screening result set through preset logic screening conditions; and carrying out weighted regression fusion on the comprehensive curative effect score and clinical detection data, and outputting a patient curative effect index. In an item weight determination process, dynamic balance between subjective experience and objective statistical information is realized through a mixed weighting model, and the defects of strong subjectivity of expert scoring and large result fluctuation in a traditional method are overcome.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating answers to medical questions using neural networks and other components. In one aspect, a method includes: obtaining question data representing a medical question; obtaining a plurality of document snippets from a medical database that stores medical documents; for each document snippet in the plurality of document snippets, determining a relevance score for the document snippet by using a ranking neural network based on the document snippet and the medical question; selecting, based at least in part on the relevance scores, a subset of the plurality of document snippets; generating a prompt that includes (i) the medical question and (ii) the subset of the plurality of document snippets; and generating an answer to the medical question based on processing the prompt using a generative neural network.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating answers to medical questions using neural networks and other components. In one aspect, a method includes: obtaining question data representing a medical question; obtaining a plurality of document snippets from a medical database that stores medical documents; for each document snippet in the plurality of document snippets, determining a relevance score for the document snippet by using a ranking neural network based on the document snippet and the medical question; selecting, based at least in part on the relevance scores, a subset of the plurality of document snippets; generating a prompt that includes (i) the medical question and (ii) the subset of the plurality of document snippets; and generating an answer to the medical question based on processing the prompt using a generative neural network.

The present disclosure provides concepts for searching a medical database comprising electrocardiogram (ECG) data. The method includes obtaining a database comprising a plurality of subject entries, each corresponding to a historic subject and comprising recorded metadata describing characteristics of the respective subject and a recorded vector embedding representing ECG data of the respective subject. A query vector embedding representing ECG data of a query subject is generated with an ECG encoder. The recorded metadata of the plurality of subject entries is compared with query metadata describing characteristics of the query subject, and the recorded vector embeddings are compared with the query vector embedding. One or more similar subject entries are identified based on a result of the comparison. Accordingly, the invention provides a searching means that is designed to take into account characteristics of subjects to identify subjects with similar cardiological conditions, thereby reducing a burden on a clinician whilst reducing a rate of misdiagnosis. For example, this may be particularly useful for triaging subjects.

The invention provides a clinical test target information extraction method and device, computer equipment and a computer readable storage medium. The method comprises the steps of obtaining a clinical test text; inputting the clinical test text into a trained target information extraction model, and outputting target field information in the clinical test text; wherein the trained target information extraction model is obtained by training preset label contents and a medical knowledge graph, and the preset label contents comprise indications, stages, pathologies, biomarkers, baseline features, treatment threads and scheme elements; and if the target field information is valid field information, summarizing the valid field information to construct a medical database. By adopting the method, the extraction efficiency of the clinical test target information can be effectively improved.

This invention relates to a method and system for intelligent editing of medical forms. The method includes: performing version number verification in response to user-input natural language editing instructions; after successful verification, reading the corresponding original form abstract syntax tree from a medical database and inputting the natural language editing instructions and the summary information of the original form abstract syntax tree into a directed graph editing pipeline; outputting an operation instruction list or clarification request through an operation planning node, and performing multi-level verification on the operation instruction list through an operation verification node when outputting the operation instruction list; and feeding back the clarification question to the front end for visualization through a clarification return node when outputting the clarification request. After the multi-level verification is successful, executing the operation instruction list through an operation execution node to generate the target form abstract syntax tree; performing structural verification on the target form abstract syntax tree, and writing the target form abstract syntax tree into a data table after successful structural verification to obtain the target medical form.

The application relates to a data query method and device, which comprises the following steps: determining a target data cube based on a target database, a first query field in a historical query process and a conditional entropy correlation algorithm; determining a data cube meta-database based on the target data cube; the data cube meta-database comprises at least one tree branch tree node; storing the data of the parent nodes of different levels in each tree branch in the at least one tree branch into different storage nodes based on a consistent hash algorithm and the access amounts of different tree nodes; storing the data of the tree nodes with different access amounts into different virtual nodes; and searching the query result corresponding to a second query field from the corresponding storage node in response to a query request of the second query field from a user end. Therefore, simple and efficient data query of a medical database is realized.

This invention relates to the field of drug safety assessment technology, and particularly to a drug safety assessment method and system based on multi-source data fusion. The method includes: receiving the SMILES structural formulas and research information of candidate drugs; encoding the SMILES structural formulas of the candidate drugs and each combination drug to obtain molecular structure feature vectors; constructing a knowledge graph by fusing multiple public biomedical databases to obtain knowledge graph embedding vectors; performing cross-modal multi-source information fusion on the molecular structure feature vectors and knowledge graph embedding vectors to obtain a multi-source fusion representation vector; inputting the concatenated vector into a prediction model to predict and calibrate drug-drug interactions and adverse reactions, obtaining calibration confidence levels; and conducting a safety assessment of drug interactions based on indications and calibration confidence levels, generating a comprehensive safety assessment report. This invention provides a reliable reference for decision-making regarding the safety of combination drug use during the drug development stage.

An object of the system according to the embodiment is to unitarily analyze a plurality of symptoms of an individual and specify the possibility of a potential disease.SOLUTION: A system includes a symptom input part, a symptom analysis part, and a database collation part. The symptom input unit collects symptoms input by a user. The symptom analysis unit analyzes the symptoms collected by the symptom input unit. The database collation unit collates the symptom analyzed by the symptom analysis unit with the medical database.SELECTED DRAWING: Figure 1

The present disclosure provides concepts for searching a medical database comprising electrocardiogram (ECG) data. The method includes obtaining a database comprising a plurality of subject entries, each corresponding to a historic subject and comprising recorded metadata describing characteristics of the respective subject and a recorded vector embedding representing ECG data of the respective subject. A query vector embedding representing ECG data of a query subject is generated with an ECG encoder. The recorded metadata of the plurality of subject entries is compared with query metadata describing characteristics of the query subject, and the recorded vector embeddings are compared with the query vector embedding. One or more similar subject entries are identified based on a result of the comparison. Accordingly, the invention provides a searching means that is designed to take into account characteristics of subjects to identify subjects with similar cardiological conditions, thereby reducing a burden on a clinician whilst reducing a rate of misdiagnosis. For example, this may be particularly useful for triaging subjects.

According to the multi-platform medical data integration and diagnosis and treatment assistance method and system, data such as patient chatting records, behavior logs and past medical histories stored in all medical service platforms are received and subjected to normalization processing, multi-platform data matching is completed with identity information of patients as the core, and a patient identity mapping table is established to achieve full-platform data association; during diagnosis and treatment, corresponding full-platform patient data are retrieved from a patient identity mapping table through patient identity information, disease information is accurately extracted based on an SOAP medical framework, a medical record first draft is automatically generated in combination with a medical knowledge base, and preliminary diagnosis and treatment suggestions have scientific basis and clear confidence by taking an evidence-based medical database as a support; a closed loop from data integration to clinical application is realized, accurate and efficient diagnosis and treatment decision support is provided for medical staff, normalization and accuracy of diagnosis and treatment services are promoted, and misdiagnosis and missed diagnosis risks are reduced.

A brain-like auxiliary diagnosis and treatment method for rare diseases is realized based on a GPU or NPU server, a system review agent is used as a sensing front end of the method, is connected with an external medical database through a standard API interface, executes automatic retrieval and quality preliminary screening of literatures, and outputs an original literature set; the document processing agent is used for receiving an original document set of the system review agent, performing structured extraction on an unstructured PDF document by utilizing a deep analysis tool, and generating a structured knowledge base containing a core clinical field; and the NHSC brain-like agent adopts a brain-like architecture based on a dual processing theory, receives the structured knowledge base and the patient data of the document processing agent, and outputs a final dynamic diagnosis and treatment suggestion through fast and slow dual-channel cooperative processing. Algorithm evaluation of evidence quality is realized, an evidence screening mechanism is enhanced from the source, risks caused by illusion of a large language model are effectively reduced, and stability and reliability of an evidence synthesis result are guaranteed.

The present application relates to the technical field of drug safety evaluation, and particularly relates to a drug safety evaluation method and system based on multi-source data fusion, comprising the following steps: receiving SMILES structural formula and research information of a candidate drug, encoding the SMILES structural formula of the candidate drug and each combination drug to obtain a molecular structure feature vector; fusing multi-source public biomedical databases to construct a knowledge graph and obtain a knowledge graph embedding vector; performing cross-modal multi-source information fusion on the molecular structure feature vector and the knowledge graph embedding vector to obtain a multi-source fusion representation vector; inputting the multi-source fusion representation vector into a prediction model after splicing to perform drug-drug interaction and adverse reaction prediction and calibration, and obtaining a calibration confidence; based on the indications and the calibration confidence, performing safety evaluation on the drug interaction, and generating a comprehensive safety evaluation report. The technical scheme of the present application can provide reliable reference for joint drug safety decision-making in the drug research and development stage.