Invention Grant
- Patent Title: Machine learning for amyloid and tau pathology prediction
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Application No.: US16580632Application Date: 2019-09-24
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Publication No.: US11621087B2Publication Date: 2023-04-04
- Inventor: Benjamin Goudey , Annalisa Jean Swan , Noel Garry Faux , Roslyn Hickson , Christine Schieber , Bowen Fung
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Patterson + Sheridan, LLP
- Main IPC: G16H50/70
- IPC: G16H50/70 ; G16H50/30 ; G06N20/00 ; G16H70/60 ; G16H50/00 ; G06K9/62 ; G06N5/00

Abstract:
Method and apparatus for predicting amyloid beta (Aβ) and phosphorylated tau (p-tau) biomarker levels in the cerebrospinal fluid (CSF) of patients. Embodiments include determining current values for a plurality of easily-measurable attributes of a first patient. Embodiments include analyzing data associated with a cohort of patients having known measurements of Aβ and p-tau biomarker levels, including determined values for the plurality of easily-measureable attributes. Embodiments include generating a predicted value for Aβ and/or p-tau biomarker levels for the first patient. Embodiments include generating a risk of the first patient developing AD at a future time, generating a probability of a patient's predicted rate of decline, and/or generating a probability of a patient's age at the onset of dementia, based on the predicted values for Aβ and/or p-tau biomarker levels.
Public/Granted literature
- US20210090746A1 MACHINE LEARNING FOR AMYLOID AND TAU PATHOLOGY PREDICTION Public/Granted day:2021-03-25
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