Data-Driven Approach for Bio-medical and Healthcare

Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He also holds a position of Adjunct Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his PhD from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence , IGI Global, USA. He is the Series Co-Editor of  Springer Tracts in Nature-Inspired Computing (Springer Nature), Data-Intensive Research(Springer Nature),  Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier) etc. He is an associate editor of  IET Image Processing and editorial board member of Complex & Intelligent Systems, Springer Nature, Applied Soft Computing, Elsevierand a Senior member of IEEE.

Chapter 1. Personal Health Record Data-Driven Integration of Heterogeneous Data.- Chapter 2. Privacy issues in data-driven healthcare.- Chapter 3. Personalizing the Patient Discharge Process and Follow Up Using Machine Learning Algorithms, Assessment Questionnaires and Ontology Reasoning.- Chapter 4. Explaining decisions of quantum algorithm: patient specific features explanation for epilepsy disease.- Chapter 5. Bioinformatics study for determination of the binding efficacy of heme-based protein.- Chapter 6. Growth Trend of Swine Flu and Covid 19 Pandemic A_ected Patients using Fuzzy Cellular Automata: A Study.- Chapter 7. Data-driven approach study for the prediction and detection of infectious disease outbreak.- Chapter 8. Design and development of interactive, real time dashboard to understand COVID-19 situation in Pune.- Chapter 9. Analyzing The Impact of Covid-19 and Vaccination using Machine Learning and ANN.- Chapter 10. Development of Psychiatric COVID-19 CHATBOT using Deep Learning.- Chapter 11. Adv nced Mathematical Model to Measure the Severity of any Pandemics.- Chapter 12. Semi-Structured Patient Data in Electronic Health Record.