Cancer Prediction for Industrial IoT 4.0 : A Machine Learning Perspective (Chapman & Hall/crc Internet of Things)

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Cancer Prediction for Industrial IoT 4.0 : A Machine Learning Perspective (Chapman & Hall/crc Internet of Things)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 203 p.
  • 言語 ENG
  • 商品コード 9781032028798
  • DDC分類 616.99400285

Full Description

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.

Contents

1. Investigation of IOMT based Cancer Detection and Prediction. 2. Histopathological Cancer Detection using CNN. 3. Role of Histone Methyltransferase In Breast Cancer. 4. Breast Cancer Detection Using Machine Learning and Its Classification. 5. Diagnosis & Prediction of Type- 2 Chronic Kidney Disease Using Machine Learning Approaches. 6. Behavioural Prediction of Cancer using Machine Learning. 7. Prediction of cervical cancer using machine learningAshish Kumar. 8. Applications of Machine Learning in Cancer prediction and Prognosis. 9. Significant advancements in cancer diagnosis using machine learning. 10. Human papillomavirus and cervical cancer. 11. Case Studies/ Success Stories on Machine Learning and Data Mining for Cancer Prediction

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