Data Science and Artificial Intelligence for Digital Healthcare

This book explores current research and development in the area of digital healthcare using recent technologies such as data science and artificial intelligence. The authors discuss how data science, AI, and mobile technologies provide the fundamental backbone to digital healthcare, presenting each technology separately as well covering integrated solutions. The book also focuses on the integration of different multi-disciplinary approaches along with examples and case studies. In order to identify the challenges with security and privacy issues, relevant block chain technologies are identified and discussed. Social aspects related to digital solutions and platforms for healthcare are also discussed and analyzed. The book aims to present high quality, technical contributions in the field of mobile digital healthcare using technologies such as AI, deep learning, IoT and distributed cloud computing.

Discusses how data science, AI, and mobile technologies provide the fundamental backbone to digital healthcare Presents a multi-disciplinary approach to the field, providing a comprehensive range of topics relevant to wide audience Relevant to researchers, scientists, computer experts, scholars and health practitioners

Autorentext
Dr. Pradeep Kumar Singh is currently working as an Associate Professor of Computer Science and Engineering at Central University of Jammu, J&K, India. Dr. Singh is a Senior member of Computer Society of India (CSI), IEEE, ACM and Life Member. He is Associate Editor of the International Journal of Information System Modeling and Design (IJISMD), Indexed by Scopus and Web of Science. He is also associate editor of International Journal of Applied Evolutionary Computation (IJAEC), IGI Global USA, Security and Privacy, Wiley. He has received three sponsored research projects grant from Govt. of India and Govt. of HP worth Rs 25 Lakhs. He has edited a total 24 books from Springer and Elsevier. He has Google scholar citations 3100, H-index 30 and i-10 Index 70. His recently published book titled Handbook of Wireless Sensor Networks: Issues and Challenges in Current Scenario's from Springer has reached more than 27000 downloads in last few months. Recently, Dr. Singh has been nominated as a Section Editor for Discover IoT, a Springer Journal. He has total eight patents to his credit, and supervised six PhD scholars as PhD Supervisor or Co-Supervisor. Prof. Marcello Trovati obtained his PhD in Mathematics at the University of Exeter in 2007, specialising in theoretical dynamical systems with singularities, after which he accepted a position as algorithm tester and research specialist at a medium sized software development company. His main responsibility was to create, test and documents state-of-the-art statistical algorithms to analyse big datasets. He then moved to the newly created Dublin IBM Research Lab to carry out research mainly in the field of knowledge discovery, text mining, and mathematical modelling, where he gained valuable business and research experience through collaboration with several scientists both at IBM, and at academic institutions. He was involved in a number of research projects in collaboration with other IBM Research Centres and academic institutions. He then joined Coventry University to take up a position as Teaching Fellow, and subsequently the University of Derby as a lecturer, during which he was involved various multi-disciplinary projects focussing on mathematical modelling, algorithm design, and big data analytics. In 2016 Marcello joined the Computer Science Department at Edge Hill University as a senior lecturer and he was recently awarded a Professorship in Computer Science. He is involved in several research themes and projects. He is co-leading the STEM Data Research centre and is actively involved in the Productivity and Innovation Lab, aiming to collaborate and support SMEs in Lancashire. Marcello's main interests include: Mathematical Modelling, Data Science, Big Data Analytics, Network Theory, Machine Learning, Data and Text Mining.

Prof. Fionn Murtagh has a strong track record in research with industrially-relevant consequences, and in teaching and learning. For over 35 years he has been a global leader in research, and applications, of clustering and data analysis, computational statistics, and also modelling and statistical analysis in image and signal processing. Fionn is editor-in-chief of Computer Journal, the British Computer Society's flagship journal. He has a leading role in classification societies International Association for Statistical Computing and the British Computer Society, and has been president of both the Classification Society of North America and the British Classification Society. He is an elected member of the Royal Irish Academy and Academia Europaea.

Dr. Mohammed Atiquzzaman obtained his M.S. and Ph.D. in Electrical Engineering and Electronics from the University of Manchester (UK) and B.S. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology. He currently holds the Edith Kinney Gaylord Presidential profes

Inhalt
Introduction.- PART-1: PANDEMIC MODELS USING DATA SCIENCE AND ARTIFICIAL INTELLIGENCE.- Data science for preventive care.- Artificial intelligence and deep learning for epidemic models.- Data analytics and cognitive computing for mobile digital health.- Multimedia big data for digital health and related topics.- PART-2: ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN HEALTHCARE 4.0.- Artificial intelligence and deep learning for clinical diagnosis.- AI- supported healthcare in IoT-cloud based platforms.- AI- empowered big data analytics and cognitive computing for smart health monitoring.- AI and ML techniques for intelligent mobile digital health solutions.- PART-3: IoT, EDGE/FOG AND CLOUD IN DIGITAL HEALTHCARE.- Wireless sensor networks & IoT for digital health.- Internet of Medical Things (IoMT) in digital health.- Advanced AIIoT convergent services, systems, infrastructure, and techniques for healthcare.- AI-supported IoT data analytics for smart healthcare.- Fog/edge Computing for digital health.- PART-4: DISTRIBUTED LEDGER AND SECURITY SOLUTIONS FOR DIGITAL HEALTHCARE RECORDS.- Block chain based electronic health record.- Blockchain for digital health Security.- Cyber Physical Systems for digital healthcare records.- Cryptography and other security solutions for the digital healthcare.- PART-5: INNOVATIVE SOLUTIONS IN MOBILE DIGITAL HEALTHCARE.- Computer aided detection and diagnosis.- Elderly smart health monitoring environments and related topics.- Conclusion. <p