Arizona State University

Mayo Foundation for Medical Education and Research

Nathan Gaw

Teresa Wu

Jing Li

Kristin R Swanson

Leland S Hu

Hyunsoo Yoon

Andrea Hawkins-Daarud

Described here are systems and methods for generating and implementing a hybrid machine learning and mechanistic model to produce biological feature maps, or other measurements of biological features, based on an input of multiparametric magnetic resonance or other images. The hybrid model can include a combination of a machine learning model and a mechanistic model that takes as an input multiparametric MRI, or other imaging, data to generate biological feature maps (e.g., tumor cell density maps), or other measures or predictions of biological features (e.g., tumor cell density). The hybrid models have capabilities of learning individual-specific relationships between imaging features and biological features.

Methods for using machine learning and mechanistic models for biological feature mapping with multiparametric MRI

Growing community of inventors

Tempe, AZ, United States of America

Nathan Gaw