Advanced Machine Learning Approaches in Cancer Prognosis - Challenges and Applications (Hardcover, 1st ed. 2021)

This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Intelligent Systems Reference Library, 204
Release date:	May 2021
First published:	2021
Editors:	Janmenjoy Nayak • Margarita N. Favorskaya • Seema Jain • Bighnaraj Naik • Manohar Mishra
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	454
Edition:	1st ed. 2021
ISBN-13:	978-3-03-071974-6
Categories:	Books > Medicine > General issues > Medical equipment & techniques > Medical research Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Medicine > Clinical & internal medicine > Diseases & disorders > Oncology > General
LSN:	3-03-071974-X
Barcode:	9783030719746

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