Artificial Intelligence-based Radiomics in the Era of Immuno-oncology.

ABSTRACT: The recent, rapid advances in immuno-oncology have revolutionized cancer treatment and spurred further research into tumor biology. Yet, cancer patients respond variably to immunotherapy despite mounting evidence to support its efficacy. Current methods for predicting immunotherapy response are unreliable, as these tests cannot fully account for tumor heterogeneity and microenvironment. An improved method for predicting response to immunotherapy is needed. Recent studies have proposed radiomics-the process of converting medical images into quantitative data (features) that can be processed using machine learning algorithms to identify complex patterns and trends-for predicting response to immunotherapy. Because patients undergo numerous imaging procedures throughout the course of the disea

SUBMITTER: Kang CY 

PROVIDER: S-EPMC9177100 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature