EXPERIENCE ENGINE-METHOD AND APPARATUS OF LEARNING FROM SIMILAR PATIENTS

A computer-implemented method of providing a treatment recommendation tailored to an untreated patient based on records of treated patients, and a similarity-based treatment system configured for performing said method, the method comprising: storing (201), in a database, the records for the treated...

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Bibliographic Details
Main Authors SRIVASTAVA, Gitika, RAMARAJAN, Naresh
Format Patent
LanguageEnglish
French
German
Published 08.02.2023
Subjects
HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
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Summary:A computer-implemented method of providing a treatment recommendation tailored to an untreated patient based on records of treated patients, and a similarity-based treatment system configured for performing said method, the method comprising: storing (201), in a database, the records for the treated patients, each record including a plurality of data elements including at least one treatment and at least one clinical diagnosis, wherein continuously new data elements are added; receiving (205) a context for treating the untreated patient and a record of the untreated patient; adjusting definitions of individual data elements and inferences; identifying (210) a group of patients that received treatment in the same context as the untreated patient; generating (215) a similarity map that minimizes a variance of data elements among the group of patients, thereby revealing non-linear similarities between the data elements; determining (220) similarity distances between the untreated patient and the group of patients using data elements from the record of the untreated patient; selecting (225) patients from the group of patients that are within a predetermined similarity distance of the untreated patient; identifying (230) the treatment to recommend to the untreated patient, wherein the method further comprises learning, by a machine learning system, non-linear similarities, wherein patients are grouped based on one or more data elements of interest, and the records of this group are processed to learn linear and non-linear similarities of various combinations of other data elements.
Bibliography:Application Number: EP20220198396