Advanced Machine Learning for Complex Medical Data Analysis
eBook - ePub

Advanced Machine Learning for Complex Medical Data Analysis

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

Advanced Machine Learning for Complex Medical Data Analysis

About this book

Advanced Machine Learning for Complex Medical Data Analysis is a definitive guide to leveraging machine learning to solve critical challenges in medical data analysis. This book discusses cutting-edge methodologies, from predictive modeling to neural networks, tailored to address the unique complexities of medical and healthcare data. It combines theoretical frameworks with practical applications, ensuring readers gain a comprehensive understanding of both concepts and real-world implementations.
The book covers diverse topics, including medical image denoising, the transformative role of GANs, IoT applications in healthcare, early disease detection using speech data, and COVID detection using autoencoders. It also explores the impact of big data, statistical approaches to medical analytics, and public health improvements through technology. Key Features:
- Practical insights into deploying advanced machine learning models for healthcare.
- Real-world case studies on diverse diseases and datasets.
- Cutting-edge topics like explainable AI, federated learning, and ethical considerations.
- Methods for improving data accuracy, efficiency, and privacy. Readership: Researchers, academics, graduate students, and professionals in data science, bioinformatics, and healthcare analytics.

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Yes, you can access Advanced Machine Learning for Complex Medical Data Analysis by Saumendra Kumar Mohapatra,Mihir Narayan Mohanty,Rashmita Khilar in PDF and/or ePUB format, as well as other popular books in Medicine & Internal Medicine & Diagnosis. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Bentham Science Publishers
Year
2025
eBook ISBN
9789815313383
Edition
0
Topic
Medicine
Subtopic
Internal Medicine & Diagnosis

Table of contents

  1. Welcome
  2. Table of Contents
  3. Title
  4. BENTHAM SCIENCE PUBLISHERS LTD.
  5. FOREWORD
  6. PREFACE
  7. List of Contributors
  8. Computational Intelligence Approaches to Predictive Modeling in Clinical Dataset Issues and Challenges: A Review
  9. Fractional Diffusion Equation for Image Denoising Utilizing C-N-R Approximation Scheme
  10. Revolutionizing Medical Imaging: The Transformative Role of Generative Adversarial Networks (GANs)
  11. Big Data in Health Care: Opportunities, Challenges and Future Direction
  12. Applications of IoT in Biomedical Engineering
  13. A Neural Network Approach for Early Detection of Parkinson’s Disease from Speech Data Using Linear and Nonlinear Dynamic Features
  14. Detecting COVID From CT Images using Autoencoders
  15. Improvement in Public Health through Technology
  16. Statistical Approach-Based Medical Data Analytics