Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare

Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that the next generation healthcare services are sprouting towards. These digital technologies can transform various aspects of healthcare, leveraging advances in computing and communication power. With a new spectrum of business opportunities, AI-powered healthcare services would improve the lives of patients, their families, and societies. However, the application of AI in the healthcare field requires special attention given the direct implication with human life and well-being. Rapid progress in AI leads to the possibility of exploiting healthcare data for designing practical tools for automated diagnosis of chronic diseases such as dementia and diabetes. This book highlights the current research trends in applying AI models in various disease diagnoses and prognoses to provide enhanced healthcare solutions. The primary audience of the book will be postgraduate students and researchers in the broad domain of healthcare technologies. Features In-depth coverage of the role of AI in smart healthcare. Research guideline for AI and data science researchers/practitioners interested in the healthcare sector. Comprehensive coverage on security and privacy issues for AI in smart healthcare. Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that the next generation healthcare services are sprouting towards. Cover 1 Half Title 2 Title Page 4 Copyright Page 5 Contents 6 Preface 8 Editors 10 Contributors 12 Chapter 1: Introduction to Artificial Intelligence (AI) for Disease Diagnosis and Prognosis in Smart Healthcare 16 Chapter 2: Machine Learning for Disease Assessment 22 Chapter 3: Precision Medicine and Future Healthcare 50 Chapter 4: AI-Driven Drug Response Prediction for Personalized Cancer Medicine 60 Chapter 5: Skin Disease Recognition and Classification Using Machine Learning and Deep Learning in Python 86 Chapter 6: COVID-19 Diagnosis-Based Deep Learning Approaches for COVIDx Dataset: A Preliminary Survey 122 Chapter 7: Automatic Grading of Invasive Breast Cancer Patients for the Decision of Therapeutic Plan 138 Chapter 8: Prognostic Role of CALD1 in Brain Cancer: A Data-Driven Review 162 Chapter 9: Artificial Intelligence for Parkinson’s Disease Diagnosis: A Review 172 Chapter 10: Breast Cancer Detection: A Survey 184 Chapter 11: Review of Artifact Detection Methods for Automated Analysis and Diagnosis in Digital Pathology 192 Chapter 12: Machine Learning-Enabled Detection and Management of Diabetes Mellitus 218 Chapter 13: IoT and Deep Learning-Based Smart Healthcare with an Integrated Security System to Detect Various Skin Lesions 234 Chapter 14: Real-Time Facemask Detection Using Deep Convolutional Neural Network-Based Transfer Learning 258 Chapter 15: Security Challenges in Wireless Body Area Networks for Smart Healthcare 270 Chapter 16: Machine Learning-Based Security and Privacy Protection Approach to Handle Physiological Data 302 Chapter 17: Future Challenges in Artificial Intelligence for Smart Healthcare 320 Index 326 Artificial;,Health,Analytics;,Healthcare;,Networking;,Smart,Healthcare;,Technology;,Data;,Machine,Learning;,Internet,of,Things Artificial,Health Analytics,Healthcare,Networking,Smart Healthcare,Technology,Data,Machine Learning,Internet of Things Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that next-generation healthcare services are sprinting towards. These digital technologies can transform various aspects of healthcare, leveraging advances in computing and communication power. With a new spectrum of business opportunities, AI-powered healthcare services will improve the lives of patients, their families, and societies. However, the application of AI in the healthcare field requires special attention given the direct implication with human life and well-being. Rapid progress in AI leads to the possibility of exploiting healthcare data for designing practical tools for automated diagnosis of chronic diseases such as dementia and diabetes. This book highlights the current research trends in applying AI models in various disease diagnoses and prognoses to provide enhanced healthcare solutions. The primary audience of the book are postgraduate students and researchers in the broad domain of healthcare technologies. Features In-depth coverage of the role of AI in smart healthcare Research guidelines for AI and data science researchers/practitioners interested in the healthcare sector Comprehensive coverage on security and privacy issues for AI in smart healthcare "Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that the next generation healthcare services are sprouting towards. These digital technologies can transform various aspects of healthcare, leveraging advances in computing and communication power. With a new spectrum of business opportunities, AI-powered healthcare services would improve the lives of patients, their families, and societies. However, the application of AI in the healthcare field requires special attention given the direct implication with human life and well-being. Rapid progress in AI leads to the possibility of exploiting healthcare data for designing practical tools for automated diagnosis of chronic diseases such as dementia and diabetes. This book highlights the current research trends in applying AI models in various disease diagnoses and prognoses to provide enhanced healthcare solutions. The primary audience of the book will be postgraduate students and researchers in the broad domain of healthcare technologies"-- Provided by publisher