Evaluation of reduction of disease risk and treatment decision

    公开(公告)号:GB2599233A

    公开(公告)日:2022-03-30

    申请号:GB202113144

    申请日:2021-09-14

    Applicant: IBM

    Abstract: Computer-implemented method 400 performed by one or more processors comprising: receiving 410 patient data of a patient; receiving 412 a selection of a disease outcome; determining 414 a risk score that the patient will experience the selected disease outcome, using the patient data; generating intervention options based on the patient data and by accessing a medical record data structure stored in a memory; determining an intervention effect for each of the intervention options, wherein the intervention effect changes the risk score; comparing the intervention effects; and providing a recommendation of at least one of the intervention options based on the comparison. The intervention effects may be determined by determining a relative risk reduction of a corresponding intervention option of the intervention options based on medical knowledge related to the corresponding intervention option. The medical knowledge may be obtained from a plurality of pieces of literature or from a plurality of studies; and each of the plurality of pieces of literature or each of the studies assigned a respective weight or variance when the intervention effect is determined. Also disclosed are a system and a computer program product.

    Automatic knowledge-based feature extraction from electronic medial records

    公开(公告)号:GB2571473A

    公开(公告)日:2019-08-28

    申请号:GB201907907

    申请日:2017-11-03

    Applicant: IBM

    Abstract: A method, device, and computer program storage product for generating a query to extract clinical features into a set of electronic medical record (EMR) tables based on clinical knowledge. A knowledge tree is constructed according to a set of clinical knowledge data. An EMR graph corresponding to a set of EMR tables is obtained. The EMR graph comprises at set of table nodes and a set of attribute nodes. The set of table nodes and the set of attribute nodes represent a structure of each EMR table in the set of EMR tables and a reference relationship among attributes of set of EMR tables. A plurality of sub-queries is generated based on the knowledge tree and the EMR graph. At least one query is generated by combining the plurality of sub-queries according to the knowledge tree.

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