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Advanced machine learning approaches in cancer prognosis [electronic resource] : challenges and applications / Janmenjoy Nayak, Margarita N. Favorskaya, Seema Jain, Bighnaraj Naik, Manohar Mishra, editors.

Nayak, Janmenjoy, editor.; Favorskaya, Margarita N., editor.; Jain, Seema, editor.; Naik, Bighnaraj, editor.; Mishra, Manohar, editor.
2021
RC262
Available Online
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Title
Advanced machine learning approaches in cancer prognosis [electronic resource] : challenges and applications / Janmenjoy Nayak, Margarita N. Favorskaya, Seema Jain, Bighnaraj Naik, Manohar Mishra, editors.
ISBN
9783030719753 (electronic bk.)
3030719758 (electronic bk.)
303071974X
9783030719746
DOI
https://doi.org/10.1007/978-3-030-71975-3
Published
Cham : Springer, 2021.
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-030-71975-3 doi
Call Number
RC262
Dewey Decimal Classification
616.99/4075
Summary
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.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed June 3, 2021).
Added Author
Nayak, Janmenjoy, editor.
Favorskaya, Margarita N., editor.
Jain, Seema, editor.
Naik, Bighnaraj, editor.
Mishra, Manohar, editor.
Series
Intelligent systems reference library ; v. 204.
Available in Other Form
Advanced machine learning approaches in cancer prognosis.
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Record Appears in
Online Resources > Ebooks
All Resources
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.

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