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Disease Prediction using Machine Learning, Deep Learning and Data Analytics

  • Book

  • March 2024
  • Bentham Science Publishers Ltd
  • ID: 5960301
This book is a comprehensive review of technologies and data in healthcare services. It features a compilation of 10 chapters that inform readers about the recent research and developments in this field. Each chapter focuses on a specific aspect of healthcare services, highlighting the potential impact of technology on enhancing practices and outcomes.

The main features of the book include 1) referenced contributions from healthcare and data analytics experts, 2) a broad range of topics that cover healthcare services, and 3) demonstration of deep learning techniques for specific diseases.

Key topics:

  • Federated learning in analysis of sensitive healthcare data while preserving privacy and security.
  • Artificial intelligence for 3-D bone image reconstruction.
  • Detection of disease severity and creating personalized treatment plans using machine learning and software tools
  • Case studies for disease detection methods for different disease and conditions, including dementia, asthma, eye diseases
  • Brain-computer interfaces
  • Data mining for standardized electronic health records
  • Data collection, management, and analysis in epidemiological research
The book is a resource for learners and professionals in healthcare service training programs and health administration departments.

Readership

Learners and professionals in healthcare service training programs and health administration departments.

Table of Contents

  • INTRODUCTION
  • DEDICATION
  • LIST OF CONTRIBUTORS
CHAPTER 1 ROLE OF FEDERATED LEARNING IN HEALTHCARE: A REVIEW
  • Geeta Rani, Meet Oza, Heta Patel, Vijaypal Singh Dhaka and Sushma Hans
  • INTRODUCTION
  • LITERATURE REVIEW
  • METHODOLOGY
  • EX

Author

  • Geeta Rani
  • Vijaypal Singh Dhaka
  • Pradeep Kumar Tiwari