Genomics models in radiotherapy: From mechanistic to machine learning.
Genomics models in radiotherapy: From mechanistic to machine learning.
Med Phys. 2020 Jun;47(5):e203-e217
Authors: Kang J, Coates JT, Strawderman RL, Rosenstein BS, Kerns SL
Abstract
Machine learning (ML) provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While ML is often applied for imaging problems in medical physics, there are many efforts to apply these principles to biological data toward questions of radiation biology. Here, we provide a review of radiogenomics modeling frameworks and efforts toward genomically guided radiotherapy. We first discuss medical oncology efforts to develop precision biomarkers. We next discuss similar efforts to create clinical assays for normal tissue or tumor radiosensitivity. We then discuss modeling frameworks for radiosensitivity and the evolution of ML to create predictive models for radiogenomics.
PMID: 32418335 [PubMed - in process]
Source: Health Physics - Category: Physics Authors: Kang J, Coates JT, Strawderman RL, Rosenstein BS, Kerns SL Tags: Med Phys Source Type: research