- Patent Title: Leveraging deep contextual representation, medical concept representation and term-occurrence statistics in precision medicine to rank clinical studies relevant to a patient
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Application No.: US17102292Application Date: 2020-11-23
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Publication No.: US12159722B2Publication Date: 2024-12-03
- Inventor: Nut Limsopatham , Liang Du , Robin Abraham
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: RAY QUINNEY & NEBEKER P.C.
- Agent Adam K. Richards
- Main IPC: G16H50/70
- IPC: G16H50/70 ; G06F40/30 ; G06N3/08 ; G16H10/60 ; G16H50/50

Abstract:
A relevance system ranks a set of medical studies based on a relevance of each medical study in the set of medical studies to a patient profile. The relevance system includes a relevance model. The relevance model determines a relevance of each medical study to the patient profile based on a semantic relationship score, a concept relationship score, and a term-occurrence score. The semantic relationship score is a measure of a similarity in semantic meaning of a medical study and a patient profile. The concept relationship score is a measure of the closeness of medical concepts in a medical study to medical concepts in a patient profile. The term-occurrence score is a measure of occurrences of terms in a medical study that also appear in a patient profile and the statistical significances of the terms.
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