Machine-learning-enabled predictive biomarker discovery and patient stratification using standard-of-care data
US12299884B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 14, 2024 |
| Grant date | May 13, 2025 |
| Priority date | — |
| Expiry date | Feb 14, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20081
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates generally to biomarker discovery and patient stratification, and more specifically to machine learning techniques for discovering relevant biomarkers using data collected as part of the standard-of-care (SoC), which can be used to identify a relevant patient population for a therapeutic with a known mechanism of action (MoA). An exemplary method for predicting activity of a molecular analyte of a patient comprises: training a first module of a machine learning model based on a plurality of medical images of a first cohort; training a second module of the machine learning model based on one or more molecular analyte data sets obtained from a second cohort; receiving a medical image from the patient; and predicting, using the trained first and second modules of the machine learning model, the activity of the molecular analyte from the medical image of the patient.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.