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

Hardback (31 Dec 2021)

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Publisher's Synopsis

Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines.

Features

 Covers the fundamentals, history, reality and challenges of cancer

 Presents concepts and analysis of different cancers in humans

 Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer

 Offers real-world examples of cancer prediction

 Reviews strategies and tools used in cancer prediction

 Explores the future prospects in cancer prediction and treatment

Readers will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions.

This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.

Book information

ISBN: 9781032028781
Publisher: CRC Press
Imprint: Chapman & Hall/CRC
Pub date:
DEWEY: 616.99400285
DEWEY edition: 23
Language: English
Number of pages: 203
Weight: 548g
Height: 254mm
Width: 178mm
Spine width: 14mm