Author : Chandrima Sinha Roy 1
Date of Publication :22nd July 2023
Abstract: Experts have anticipated the promise of highly individualised oncology care using artificial intelligence (AI) technology since the field's start. Numerous scientific advancements have made this promise a reality, including enhanced deep learning and machine learning algorithms, deeper multiomics databases, and lower costs for massively parallelized computer power. There are examples of effective clinical applications of AI across the cancer continuum and in transdisciplinary practise, with computer vision-assisted image analysis in particular having a number of U.S. Food and Drug Administration-approved uses. Natural language processing to predict health trajectories from medical records, virtual biopsies, whole blood multicancer detection via deep sequencing, and advanced clinical decision support systems that incorporate genomics and clinomics are some of the techniques with growing practical utility.
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