Advanced Prognostic Predictive Modelling in Healthcare Data Analytics

Dr. Sudipta Roy has received his Ph.D. in Computer Science & Engineering from the Department of Computer Science and Engineering, University of Calcutta. He is an author of more than forty publications in refereed national/international journals and conferences including IEEE, Springer, Elsevier and many others. He is an author of one book and many book chapters. He holds an US patent in medical image processing and filed an Indian patent in smart agricultural system. He has served as a reviewer of many international journals including IEEE, Springer, Elsevier, IET and many others, and international conferences. He has served as an international advisory committee member and a program committee member of AICAE-2019, INDIACom-2019, CAAI 2018, ICAITA-2018, ICSESS-2018, INDIACom-2018, ISICO-2017, AICE-2017 and many more conferences. He is serving as Associate Editor of IEEE Access, IEEE and International Journal of Computer Vision and Image Processing (IJCVIP), IGI Global Journal. He has more than five years of experience in teaching and research. His fields of research interests are healthcare image analysis, image processing, steganography, artificial intelligence, big data analysis, machine learning and big data technologies. Currently, he is working at PRTTL, Washington University in St. Louis, Saint Louis, MO, USA. Dr. Lalit Mohan Goyal has completed Ph.D. from Jamia Millia Islamia, New Delhi, in Computer Engineering, M.Tech. (Honours) in Information Technology from Guru Gobind Singh Indraprastha University, New Delhi, and B.Tech. (Honours) in Computer Engineering from Kurukshetra University, Kurukshetra. He has 16 years of teaching experience in the area of theory of computation, parallel and random algorithms, distributed data mining & cloud computing. He has completed a project sponsored by Indian Council of Medical Research, Delhi. He has also published research papers in SCI indexed & Scopus indexed journals and conferences. He is areviewer of many reputed journals & conferences also. Presently, he is working at J. C. Bose University of Science & Technology, YMCA, Faridabad, in the Department of Computer Engineering.Dr. Mamta Mittal graduated in Computer Science & Engineering from Kurukshetra University Kurukshetra in 2001 and received master’s degree (Honours) in Computer Science & Engineering from YMCA, Faridabad. She has completed her Ph.D. from Thapar University Patiala in Computer Science and Engineering. She has been teaching from the last 16 years with emphasis on data mining, machine learning, soft computing and data structure. She is a lifetime member of CSI. She has published and communicated number of research papers in SCI, SCIE and Scopus indexed Journals and attended many workshops, FDPs and Seminars. She has filed two patents – one is on human surveillance system and another is on wireless copter for explosive handling and diffusing. Presently, she is working at G.B. Pant Government Engineering College, Okhla, New Delhi (under Government of NCT Delhi), and supervising Ph.D. candidates of GGSIPU (Guru Gobind Singh Indraprastha University), Dwarka, New Delhi. She is Main Editor of the Book entitled “Data Intensive Computing Application for Big Data” published by IOS Press, Netherland, and another Book entitled “Big Data Processing Using Spark in Cloud” by Springer. She is Managing Editor of International Journal of Sensors, Wireless Communications and Control Published by Bentham Science. She is working on DST approved Project “Development of IoT based hybrid navigation module for mid-sized autonomous vehicles” and Handing Pradhan Mantri YUVA project for Entrepreneur Cell Activity as Faculty Coordinator/Representative from G.B. Pant Government Engineering College. She is a reviewer of many reputed journals, chaired number of conferences and delivered invited talks.

“The book offers a collection of literature review, and discussions of the methods in computer sciences, artificial intelligence, machine learning and may offer materials for graduate students in biomedical engineering and healthcare communications. I certainly will recommend this book for individuals in data and predictive modelling especially when they are quantitatively inclined as the prognostic modelling techniques rely on mathematical and or statistical formulations.” (Reuben Adatorwovor, ISCB News, iscb.info, June, 2022)

• Data visualization in the transformation of healthcare industries.- Emerging Healthcare Problems in High Dimensional Data and Dimension Reduction.- Disease Prediction Using Data Mining and Machine Learning Techniques.- Prognostic modeling with the internet of Healthcare things applications.- Cancer Tissue Segmentation in Various Conditions with Semiautomatic and Automatic Approach.- Early Screening of COVID-19 from Chest CT using Deep Learning Technique.- Clinical Decision-Making and Predicting Patient Trajectories.