Machine learning-based diagnostic classifier

US11676732B2 · kind B2 · utility

Assignee

• Neumora Therapeutics, Inc. · US

Inventors

• Monika Sharma Mellem · San Francisco, US
• Yuelu Liu · San Francisco, US
• Parvez Ahammad · San Jose, US
• Humberto Andres Gonzalez Cabezas · Santa Clara, US
• William John Martin · Apex, US
• Pablo Christian Gersberg · San Francisco, US

Key dates

• Filing date: Sep 1, 2021
• Grant date: Jun 13, 2023
• Expiry date: Sep 19, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H50/20
• WIPO field: Medical technology
• WIPO sector: Instruments

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.