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OverviewThis book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques, which are essential to cancer diagnostics. Topics include introduction to current applications of deep learning in cancer diagnostics, pre-processing of cancer data using deep learning, review of deep learning techniques in oncology, overview of advanced deep learning techniques in cancer diagnostics, prediction of cancer susceptibility using deep learning techniques, prediction of cancer reoccurrence using deep learning techniques, deep learning techniques to predict the grading of human cancer, different human cancer detection using deep learning techniques, prediction of cancer survival using deep learning techniques, complexity in the use of deep learning in cancer diagnostics, and challenges and future scopes of deep learning techniques in oncology. Full Product DetailsAuthor: Jyotismita Chaki , Aysegul UcarPublisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.440kg ISBN: 9781032233857ISBN 10: 1032233850 Pages: 167 Publication Date: 22 February 2023 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationJyotismita Chaki, PhD, is an Associate Professor at School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India. Aysegul Ucar, PhD, is a Professor in Department of Mechatronics Engineering, Firat University, Turkey. Tab Content 6Author Website:Countries AvailableAll regions |