Artificial Intelligence revolution in Oncology

Artificial intelligence (AI) has contributed substantially to the resolution of a spread of biomedical problems, including cancer, over the past decade. Deep learning, a subfield of AI that's highly flexible and supports automatic feature extraction, is increasingly being applied in various areas of both basic and clinical cancer research. The successful translation of AI (AI) applications into clinical cancer care practice requires guidance by academic cancer researchers and providers who are well poised to step into leadership roles. These breakthroughs have allowed deep learning to be adopted as an approach which will efficiently solve various problems in biomedicine. The appliance of deep learning to the diagnosis of diseases on the idea of the classification of radiological or pathological images has demonstrated a performance that equals or actually exceeds that of clinical experts. During this rapidly developing field, there are few established standards, and oncology researchers and providers must educate themselves about emerging AI technology to avoid common pitfalls and ensure responsible use.

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Media Contact:  

Alice Nicholas          

Journal Manager

American Journal of Computer Science and Engineering Survey

Email: computersci@scholarlymed.com