Current Applications of Deep Learning in Cancer Diagnostics - Rilegato

Rilegato

ISBN 10: 1032233850 ISBN 13: 9781032233857

Casa editrice: CRC Press, 2023

Riassunto

This 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.

Su questo libro

Informazioni sull'autore

Jyotismita 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.

Dalla quarta di copertina

This book demonstrates the core concepts of deep learning algorithms that, using diagrams, data tables, and examples, are especially useful for deep learning based human cancer diagnostics.

Dettagli dell'edizione

• Editore: CRC Press
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 1032233850
• ISBN 13: 9781032233857
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 167
• Redattore: Chaki Jyotismita, Ucar Aysegul
• Contatto del produttore: Taylor and Francis, GPSR Taylor and Francis; gpsr@taylorandfrancis.com; ; Taylor & Francis Verlag GmbH, Kaufingerstraße 24; München; 80331; Germania