- Patent Title: Machine learning systems for processing multi-modal patient data
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Application No.: US17960705Application Date: 2022-10-05
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Publication No.: US11670417B2Publication Date: 2023-06-06
- Inventor: Tathagata Banerjee , Matthew Edward Kollada
- Applicant: NEUMORA THERAPEUTICS, INC.
- Applicant Address: US CA San Francisco
- Assignee: Neumora Therapeutics, Inc.
- Current Assignee: Neumora Therapeutics, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Fish & Richardson P.C.
- Main IPC: G16H50/30
- IPC: G16H50/30 ; G06N3/08 ; G16H20/60 ; G16H40/20 ; G16H50/70 ; G16H50/20 ; G06N3/02 ; G06N3/045 ; G16H30/40 ; G06V10/77 ; G06V10/82 ; G06V10/774 ; G06T7/00 ; G06N20/00

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying a patient. In one aspect, a method comprises: receiving multi-modal data characterizing a patient, wherein the multi-modal data comprises a respective feature representation for each of a plurality of modalities; processing the multi-modal data characterizing the patient using an encoder neural network to generate an embedding of the multi-modal data characterizing the patient; determining a respective classification score for each patient category in a set of patient categories based on the embedding of the multi-modal data characterizing the patient; and classifying the patient as being included in a corresponding patient category from the set of patient categories based on the classification scores.
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