放射基因组学
精密医学
个性化医疗
无线电技术
医学
梅德林
观点
人工智能
数据科学
医学物理学
计算机科学
生物信息学
病理
放射科
生物
艺术
视觉艺术
生物化学
作者
Sanjay Saxena,Biswajit Jena,Neha Gupta,Suchismita Das,Deepaneeta Sarmah,Pallab Bhattacharya,Tanmay Nath,Paul Sauseng,Mostafa M. Fouda,Manudeep Kalra,Luca Saba,Gyan Pareek,Jasjit S. Suri
出处
期刊:Cancers
[MDPI AG]
日期:2022-06-09
卷期号:14 (12): 2860-2860
被引量:32
标识
DOI:10.3390/cancers14122860
摘要
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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