Landscape of Pattern Learning Applied to Public Health and Social Sciences

In this book, different machine learning and deep learning-based approaches are provided in terms of public health and social science. This book demonstrates medical imaging-based cancer detection studies. Chapter One discusses a comprehensive analysis of tissue-specific colorectal cancer classification from H&E-stained microscopic images. Chapter Two demonstrates an Ensemble-Based CNN framework for Breast Cancer Detection in Mammograms. Chapter Three provides a Deep Learning-Based Tissue-Specific Classification technique of Colorectal Cancer from H&E-Stained Microscopic Images. Chapter Four describes Parkinson's Disease Detection through machine learning technique from Speech and Imaging Data. Chapter Five describes empowering social causes, i.e., Indian Language Identification with Multimodality Strategy. Moreover, this book provides innovative information about pattern recognition, feature selection and disease classification from medical imaging datasets for public and social sciences that are benevolent for healthcare persons, doctors and social science researchers.

In this book, different machine learning and deep learning-based approaches are provided in terms of public health and social science. This book demonstrates medical imaging-based cancer detection studies. Chapter One discusses a comprehensive analysis of tissue-specific colorectal cancer classification from H&E-stained microscopic images. Chapter Two demonstrates an Ensemble-Based CNN framework for Breast Cancer Detection in Mammograms. Chapter Three provides a Deep Learning-Based Tissue-Specific Classification technique of Colorectal Cancer from H&E-Stained Microscopic Images. Chapter Four describes Parkinson''s Disease Detection through machine learning technique from Speech and Imaging Data. Chapter Five describes empowering social causes, i.e., Indian Language Identification with Multimodality Strategy. Moreover, this book provides innovative information about pattern recognition, feature selection and disease classification from medical imaging datasets for public and social sciences that are benevolent for healthcare persons, doctors and social science researchers.