Cancer Prediction for Industrial IoT 4.0:A Machine Learning Perspective

Cancer Prediction for Industrial IoT 4.0:A Machine Learning Perspective (Chapman & Hall/CRC Internet of Things) 1st Edition
Author:Meenu Gupta,Rachna Jain,Arun Solanki,Fadi Al-Turjman (Editor)
Publisher Finelybook 出版社:Chapman and Hall/CRC; 1st edition (December 30, 2021)
Language 语言:English
pages 页数:216 pages
ISBN-10 书号:1032028785
ISBN-13 书号:9781032028781

Book Description
Cancer Prediction for Industrial IoT 4.0:A Mining and Machine Learning Perspective explores the various cancers using Artificial Intelligence Techniques. It presents the rapid advancement in the existing predicting models Author:applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment are incorporated in the book. The wide variety of topics it presents offers readers multiple perspectives on various disciplines, including the number of chapters in the edited book.

The key features of this Edited Book are as follows:

Fundamental, History, Reality and Challenges of Cancer
Concepts and Analysis of different cancer in human
Machine Learning-based Deep Learning and data mining Concepts in the prediction of cancer
Prediction of cancer including different real-world examples
Strategies and Tools for Prediction of cancer
Future prospectus in cancer prediction and treatment
The main benefits of reading this book are as follows:

Readers can be able to understand the fundamental concepts and analysis of Cancer prediction and treatment
Readers can learn how to apply emerging technologies such as Machine Learning into practice to tackle challenges in s domains/fields of cancer with real-world scenarios.
Help guide the reader to the specific ideas, tools, and practices most applicable to the product/service development and innovation problems and opportunities.
Hands-on chapters contributed Author:the academicians and other professionals from reputed organizations provides and describes frameworks, applications, best practices and case studies on emerging cancer treatment and predictions.
This book will help the graduates, data scientists, machine learning users, doctors and analytics Managers


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