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

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 en...

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Bibliographic Details
Published in:Cancers 2022-06, Vol.14 (12), p.2860
Main Authors: Saxena, Sanjay, Jena, Biswajit, Gupta, Neha, Das, Suchismita, Sarmah, Deepaneeta, Bhattacharya, Pallab, Nath, Tanmay, Paul, Sudip, Fouda, Mostafa M., Kalra, Manudeep, Saba, Luca, Pareek, Gyan, Suri, Jasjit S.
Format: Article
Language:English
Subjects:
Artificial intelligence
Biomarkers
Brain research
Cancer
Clinical aspects
Clinical decision making
Computer applications
Deep learning
Discriminant analysis
Genomes
Genomics
Machine learning
Mammography
Medical imaging
Medical prognosis
Medical research
Neural networks
Oncology
Patients
Phenotypes
Precision medicine
Prediction models
Probability distribution
Prognosis
Radiomics
Review
Survival
Tumors
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Summary: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.
ISSN:2072-6694
2072-6694
DOI:10.3390/cancers14122860