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Advanced Machine Learning Approaches in Cancer Prognosis = Challenges and Applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advanced Machine Learning Approaches in Cancer Prognosis/ edited by Janmenjoy Nayak, Margarita N. Favorskaya, Seema Jain, Bighnaraj Naik, Manohar Mishra.
其他題名:	Challenges and Applications /
其他作者:	Mishra, Manohar.
面頁冊數:	XX, 454 p. 236 illus., 168 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Machine Learning. -
電子資源:	https://doi.org/10.1007/978-3-030-71975-3
ISBN:	9783030719753

Advanced Machine Learning Approaches in Cancer Prognosis = Challenges and Applications /
Advanced Machine Learning Approaches in Cancer PrognosisChallenges and Applications /[electronic resource] :edited by Janmenjoy Nayak, Margarita N. Favorskaya, Seema Jain, Bighnaraj Naik, Manohar Mishra. - 1st ed. 2021. - XX, 454 p. 236 illus., 168 illus. in color.online resource. - Intelligent Systems Reference Library,2041868-4408 ;. - Intelligent Systems Reference Library,67.

Advances in Machine Learning Approaches in Cancer Prognosis -- Data Analysis on Cancer Disease using Machine Learning Techniques -- Learning from multiple modalities of imaging data for cancer detection/diagnosis -- Neural Network for Lung Cancer diagnosis -- Improved Thyroid Disease Prediction Model Using Data Mining Techniques with Outlier Detection -- Automated Breast Cancer Diagnosis Based on Neural Network Algorithms. .

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. .

ISBN: 9783030719753

Standard No.: 10.1007/978-3-030-71975-3doiSubjects--Topical Terms:

1137723
Machine Learning.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Advanced Machine Learning Approaches in Cancer Prognosis = Challenges and Applications /
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