Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare

Author: S.M. Riazul Islam, Faisal Tariq and Ghita Kouadri Mostefaoui

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Summary

Description

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

About the Author

Ghita Kouadri Mostefaoui is currently an Associate Professor at the Department of Computer Science, University College London. Her current teaching includes programming, computer architecture, and software engineering. She received her PhD in computer science from both the University of Fribourg, Switzerland and Université Pierre et Marie Curie (Paris 6). Ghita is a Fellow of the Higher Education Academy.

S. M. Riazul Islam is currently a Senior Lecturer in Computer Science at the University of Huddersfield, United Kingdom. Before moving to the UK, he was an Assistant Professor at the Department of Computer Science and Engineering, Sejong University, South Korea, from 2017 to 2022. Dr. Islam's prior affiliations were at Inha University as a Postdoctoral Fellow, at Samsung R&D Institute as a Senior Engineer, and at the University of Dhaka as an Assistant Professor in EEE. He received his Ph.D. in Information and Communication Engineering from Inha University, South Korea, in 2012. Dr. Islam's research interests include applied AI, machine learning, data science, and IoT.

Faisal Tariq is currently a Senior Lecturer at the James Watt School of Engineering, University of Glasgow, United Kingdom. He received his PhD degree from The Open University, UK. His research interests include applications of Artificial Intelligence (AI) and Machine Learning (ML) in various domains including smart wireless communications, healthcare technology, cyber security and intelligent internet of Things (IIoT). He is a senior member of IEEE and fellow of the Higher Education Academy.

More on this Book

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.