Machine Learning in Information and Communication Technology

Prof. Hiren Kumar Deva Sarma is Professor in the Department of Information Technology, Gauhati University, Assam, India. He received Bachelor of Engineering in Mechanical Engineering from Assam Engineering College, Guwahati, Assam (1998). He completed Master of Technology in Information Technology from Tezpur University, Assam (2000). He received Doctor of Philosophy (in Computer Science & Engineering) from Jadavpur University, West Bengal (2013). He has co-authored three books, edited four book volumes, and published more than eighty research papers in different International Journals and refereed International and National Conferences of repute. He is the recipient of the Young Scientist Award from International Union of Radio Science (URSI) in the XVIII General Assembly 2005, held at New Delhi, India and has received IEEE Early Adopter Award in 2014. His current research interests are networks, network security, robotics and big data analytics.     Prof. Vincenzo Piuri is an Italian scientist. He is IEEE Fellow and ACM Distinguished Scientist.  He is known for his work in the field of information processing, with specific focus on artificial intelligence, computational intelligence, signal/image processing, biometrics, industrial applications, measurement systems, arithmetic units and fault-tolerant architectures. He received his M.S. and Ph.D. in Computer Engineering from Politecnico di Milano, Italy. He is Full Professor at the University of Milan, Italy (since 2000), where he was also Department Chair (2007–2012). He was Associate Professor at Politecnico di Milano, Italy (1992–2000), Visiting Professor at the University of Texas at Austin, USA (summers 1996–1999), and visiting researcher at George Mason University, USA (summers 2012–2019). He founded a start-up company, Sensure srl, in the area of intelligent systems for industrial applications (leading it from 2007 until 2010) and was active in industrial research projects with several companies.   Prof. Arun K Pujari is Former Professor and Dean of the School of Computer and Information Sciences at the University of Hyderabad (UoH). He has been Vice-Chancellor of the Central University of Rajasthan (2015–2020) and Vice-Chancellor of Sambalpur University, Odisha (20082011). He joined the UoH as Reader in 1985 and became a professor in 1990. Prior to joining University of Hyderabad, he served JNU, New Delhi. He completed his postgraduation from the Sambalpur University in 1974 and got his Ph.D. from IIT-Kanpur in 1980. He has more than 25 years' experience as Vice-Chancellor, Dean, Head of Department, and other administrative positions. He has served several high-level bodies of UGC, DST, DRDO, ISRO and AICTE. He has wide exposure in the national and international arena, and he has been invited to University of Tokyo, Japan,University of Paris-Sud, France, Griffith University, Australia, Memphis University, USA and IIST, United Nations University, Macau on different visiting assignments. He has more than 100 publications to his credit and his book, Data Mining Techniques, was a popular textbook adopted by several universities in India and abroad.

Part 1: Healthcare Informatics.- Chapter 1. Earth Mover’s Distance Based Automated Disease Tagging of Indian ECGs.- Chapter 2. Cardial Disease Prediction in Multi-variant Systems: A Short Survey.- Chapter 3. SVM-based pre-and post-treatment cancer segmentation from lung and abdominal CT images via neighbourhood-influenced features.- Chapter 4. Blood Cancer Detection with Microscopic Images using Machine Learning.-Chapter 5. A Survey on Leukemia Detection: A Machine Learning Approach.- Chapter 6. Periocular Region Recognition - A Brief Survey.- Chapter 7. A Bibliometric Analysis on the relationship between Emotional Intelligence, Self-Management and Health Information Seeking.- Chapter 8. Preferences in the Detailing Process Among Young and Senior Physicians.- Chapter 9. Perceptual Difference Patient & Physician on Negative Aspects of Social Media.- Chapter 10. AUTCD-Net: An Automated Framework for Efficient Covid-19 Diagnosis on Computed Tomography Scans.- Chapter 11. Computer aided detection of brain midline using CT images.- Chapter 12. Deep neural network based classification of ASD and neuro-typical subjects using functional connectivity features derived from resting state fMRI data.- Chapter 13. Application of Deep Learning in Healthcare.- Part 2: Recommendation Systems.- Chapter 14. A Popularity-based Recommendation System using Machine Learning.- Chapter 15. Machine Learning based Movies and Shows Recommendation System. etc.