Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications
eBook - ePub

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

Om Prakash Jena, Bharat Bhushan, Utku Kose, Om Prakash Jena, Bharat Bhushan, Utku Kose

  1. 280 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

Om Prakash Jena, Bharat Bhushan, Utku Kose, Om Prakash Jena, Bharat Bhushan, Utku Kose

Book details
Table of contents
Citations

About This Book

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.

This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems.

Features:



  • Covers the fundamentals of ML and DL in the context of healthcare applications


  • Discusses various data collection approaches from various sources and how to use them in ML/DL models


  • Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field


  • Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics


  • Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly

This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios.

Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India.

Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India.

Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.

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Information

Publisher
CRC Press
Year
2022
ISBN
9781000533972

Table of contents

  1. Cover Page
  2. Half-Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Contents
  7. Preface
  8. Editors
  9. Contributors
  10. 1 Common Data Interface for Sustainable Healthcare System
  11. 2 Brain–Computer Interface: Review, Applications and Challenges
  12. 3 Three-Dimensional Reconstruction and Digital Printing of Medical Objects in Purview of Clinical Applications
  13. 4 Medical Text and Image Processing: Applications, Methods, Issues, and Challenges
  14. 5 Usage of ML Techniques for ASD Detection: A Comparative Analysis of Various Classifiers
  15. 6 A Framework for Selection of Machine Learning Algorithms Based on Performance Metrices and Akaike Information Criteria in Healthcare, Telecommunication, and Marketing Sector
  16. 7 Hybrid Marine Predator Algorithm with Simulated Annealing for Feature Selection
  17. 8 Survey of Deep Learning Methods in Image Recognition and Analysis of Intrauterine Residues
  18. 9 A Comprehensive Survey on Breast Cancer Thermography Classification Using Deep Neural Network
  19. 10 Deep Learning Frameworks for Prediction, Classification and Diagnosis of Alzheimer's Disease
  20. 11 Machine Learning Algorithms and COVID-19: A Step for Predicting Future Pandemics with a Systematic Overview
  21. 12 TRNetCoV: Transferred Learning-based ResNet Model for COVID-19 Detection Using Chest X-ray Images
  22. 13 The Influence of COVID-19 on Air Pollution and Human Health
  23. 14 Smart COVID-19 GeoStrategies using Spatial Network VoronoĂŻ Diagrams
  24. 15 Healthcare Providers Recommender System Based on Collaborative Filtering Techniques
  25. Index
Citation styles for Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

APA 6 Citation

[author missing]. (2022). Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications (1st ed.). CRC Press. Retrieved from https://www.perlego.com/book/3225054/machine-learning-and-deep-learning-in-medical-data-analytics-and-healthcare-applications-pdf (Original work published 2022)

Chicago Citation

[author missing]. (2022) 2022. Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications. 1st ed. CRC Press. https://www.perlego.com/book/3225054/machine-learning-and-deep-learning-in-medical-data-analytics-and-healthcare-applications-pdf.

Harvard Citation

[author missing] (2022) Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications. 1st edn. CRC Press. Available at: https://www.perlego.com/book/3225054/machine-learning-and-deep-learning-in-medical-data-analytics-and-healthcare-applications-pdf (Accessed: 15 October 2022).

MLA 7 Citation

[author missing]. Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications. 1st ed. CRC Press, 2022. Web. 15 Oct. 2022.