Deep learning methods for drug response prediction in cancer: Predominant and emerging trends.

ABSTRACT: Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predictive models to study and treat cancer holds great promise in improving drug development and personalized design of treatment plans, ultimately suppressing tumors, alleviating suffering, and prolonging lives of patients. A wave of recent papers demonstrates promising results in predicting cancer response to drug treatments while utilizing deep learning methods. These papers investigate diverse data representations, neural network architectures, learning methodologies, and evaluations schemes. However, deciphering promising predominant and emerging trends is difficult due to the variety of explored methods and lac

SUBMITTER: Partin A 

PROVIDER: S-EPMC9975164 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature