Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine

Overview

Journal Cancers (Basel)

Publisher MDPI

Specialty Oncology

Date 2022 Jun 24

PMID 35740526

Authors

Sanjay Saxena

Biswajit Jena

Neha Gupta

Suchismita Das

Deepaneeta Sarmah

Pallab Bhattacharya

Tanmay Nath

Sudip Paul

Mostafa M Fouda

Manudeep Kalra

Luca Saba

Gyan Pareek

Jasjit S Suri

Affiliations

Soon will be listed here.

Abstract

Radiogenomics, a combination of "Radiomics" and "Genomics," using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes. It has recently shown tremendous achievements in prognosis, treatment planning, survival prediction, heterogeneity analysis, reoccurrence, and progression-free survival for human cancer study. Although AI has shown immense performance in oncology care in various clinical aspects, it has several challenges and limitations. The proposed review provides an overview of radiogenomics with the viewpoints on the role of AI in terms of its promises for computational as well as oncological aspects and offers achievements and opportunities in the era of precision medicine. The review also presents various recommendations to diminish these obstacles.

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