Machine Learning for Healthcare Informatics

Techniques and Applications

Nazmul Siddique, Mohammad Shamsul Arefin, Mohammad Abu Yousuf, M. Shamim Kaiser

• Publisher: Chapman and Hall/CRC
• Year: 2026
• eBook ISBN:
  9781040705773
• Topic: Medicine
• Subtopic: Computer Science General

This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in disease diagnosis, treatment, and healthcare management. It shows that adaptation of machine learning can bring significant benefits for the sustainability of healthcare informatics in the era of 4.0 IR.

With contributions from researchers and field experts, the book covers key topics such as predictive analytics, medical image processing, and personalized healthcare. Each chapter provides detailed methodologies, datasets, and experimental results, with practical insights into AI-driven diagnostics, patient monitoring, and decision-support systems.

Designed for those seeking to apply machine learning in healthcare and to advance healthcare informatics, this book is a valuable resource for researchers, professionals, and students.

Table of contents

• Cover Page
• Half-Title Page
• Title Page
• Copyright Page
• Dedication Page
• Contents
• Preface
• Contributors
• About the Editors
• 1 A Robust Deep Learning-Based Hybrid Model to Detect COVID-19 Using Chest X-Ray
• 2 Transfer Learning-Based Approach to Detect Crop Disease Using Android Application
• 3 A Proposed Sequential Network Analysis for Identification of Hub Genes for Therapeutics in Tuberculosis and Its Overlaying Non-Communicable Diseases
• 4 Transfer-Learning-Based Feature Extractor Performance Analysis to Classify Black Gram Leaf Disease
• 5 Early Prediction of Breast Cancer Using Deep Learning Models
• 6 Chest-InfNet: A Deep Learning Architecture for Lung Diseases Detection and Infected Region Localization from Chest X-Ray Images
• 7 Ensemble-Based Transfer Learning Approach for Brain Tumor Segmentation from MRI Images
• 8 Preventing Skin Cancer through Improved Skin Lesion Recognition: An Attention-Triplet and Multi-Layer Ensemble-Based CNN Approach
• 9 Gastrointestinal Disease Classification through Explainable and Cost-Sensitive Deep Neural Networks with Supervised Contrastive Learning
• 10 COVID-19 Distance Learning Understanding Classification Using Scalogram Based on Transfer Learning and Principal Feature Classifier from EEG Signals
• 11 Large Ensemble of Transfer-Learned Models for Plant Disease Recognition from Diverse Leaf Images
• 12 Computer-Aided Strategy to Diagnose Lung Cancer from CT-Scan Images Using Inception Architecture
• 13 Bone Age Assessment Using Convolutional Neural Network with Attention Module
• 14 Toward Bengali Health Text Identification Using Deep Learning Technique
• 15 Brain Tumor Detection Using Fine-Tuned ResNet-101 on Magnetic Resonance Images
• 16 Automated Agricultural Pests Identification Using Convolutional Neural Network-Based Transfer Learning
• 17 CTFCP: A Cloud-Based Deep Transfer Learning Framework for Analyzing Chest X-Ray Images to Detect Pneumonia