Invention Publication
- Patent Title: MACHINE LEARNING-BASED DIAGNOSTIC CLASSIFIER
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Application No.: US18311087Application Date: 2023-05-02
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Publication No.: US20230343463A1Publication Date: 2023-10-26
- Inventor: Monika Sharma MELLEM , Yuelu LIU , Parvez AHAMMAD , Humberto Andres GONZALEZ CABEZAS , William J. MARTIN , Pablo Christian GERSBERG
- Applicant: NEUMORA THERAPEUTICS, INC.
- Applicant Address: US CA BRISBANE
- Assignee: NEUMORA THERAPEUTICS, INC.
- Current Assignee: NEUMORA THERAPEUTICS, INC.
- Current Assignee Address: US CA BRISBANE
- Main IPC: G16H50/30
- IPC: G16H50/30 ; G16H50/20 ; G16H10/60

Abstract:
Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions is selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.
Public/Granted literature
- US12002590B2 Machine learning-based diagnostic classifier Public/Granted day:2024-06-04
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