Decision Support System for Diabetes Healthcare: Advancements and Applications

Usha Desai is presently working as a Professor and Dean (Research & Development) for S.E.A. College of Engineering & Technology, Bengaluru. She received her Ph.D. in Biomedical Signal Processing from REVA University, Bengaluru, and M. Tech. and B.Eng. from Visvesvaraya Technological University, Belagavi, Karnataka. She received a DST International Travel Grant to present her research paper at 39th IEEE EMBS International Annual Conference held in South Korea. She has served as Session Chair in reputed IEEE International Conferences. Also, she has presented papers in many reputed conferences and authored more than 40 research publications. She has authored five books in Biomedical Healthcare. She has six patents. She is presently Senior Member of IEEE and Life Member of ISTE.Biswaranjan Acharya (Senior Member, IEEE) received his M.C.A. degree from IGNOU, New Delhi, India, in 2009, and his M.Tech. degree in computer science and engineering from the Biju Pattanaik University of Technology (BPUT), Rourkela, Odisha, India, in 2012. He is working as an Assistant Professor at the Department of Computer Engineering-AI and BDA. He has submitted his Ph.D. thesis in computer application to the Veer Surendra Sai University of Technology (VSSUT), Burla, Odisha, India. He has a total of more than ten years of experience in academia at reputed universities, such as Ravenshaw University, and in the software development field. He is the co-author of more than 70 research articles in internationally reputed journals and serves as a reviewer for many peer-reviewed journals. He has more than 50 patents to his credit. His research interests are in multiprocessor scheduling, data analytics, computer vision, machine learning, and the IoT. He is also associated with various educational and research societies, such as IACSIT, CSI, IAENG, and ISC.Dr. Madhu Shukla is Associate Professor & Head of Computer Engineering – AI & Big Data Analytics, at Marwadi University, Rajkot, Gujarat, India. She has been in the teaching field for the last 15 years. She is an Oracle Certified Trainer for Courses related to databases and PL/SQL. She completed her Ph.D. from RK University in 2019, in Rajkot. She has chaired many international conferences. She has published 50+ papers in reputed journals and conferences. She is guiding 10 Ph.D. students and has guided more than 100 UG projects. She is a Senior IEEE member and lifetime member of other professional societies.Varadraj Gurupur, Ph.D., is currently working as an associate professor in the School of Global Health Management and Informatics at the University of Central Florida. Dr. Gurupur is a recipient of two international awards, two national awards, and several regional and institutional awards. His core research is focused on software engineering decision support systems for healthcare and education. Dr. Gurupur is a recipient of research grants and has two patents in health information management. Dr. Gurupur has more than 100 publications to his name, which include: an edited book, book chapters, journal articles, conference papers, abstracts, and published reviews. His articles have been published in high impact journals and his research work is widely used by researchers across the globe. From a teaching perspective, Dr. Gurupur has more than 11 years of teaching experience and has served as a teacher in two different countries. Dr. Gurupur has also worked in the healthcare industry for several years. Based on this work experience and academic training he is involved in discovering innovative solutions to difficult problems associated with electronic health records.

• 1. Importance of Analyzing Causality for Diabetes Care. 2. Advances and Opportunities in Digital Diabetic Health Care Systems. 3. Role of IoT and Expert Systems in Diabetes Control with Continuous Diagnosis of Medical Conditions. 4. Harnessing Machine Intelligence and Big Data for Diabetes Management. 5. Machine Intelligence and Big Data in Diabetic Care: Laboratorian's Perspective. 6. EfficientNetB3-DTL: Classification of Diabetic Retinopathy Images using Modified EfficientNetB3 with Deep Transfer Learning. 7. Prediction and Diagnosis of Glaucoma in Fundus Images through Optic Cup and Optic Disk Segmentation. 8. Early Diagnosis of Diabetes using an Intelligent Machine Learning Technique. 9. Advanced Diabetes Prediction: A Comprehensive Analysis of Machine Learning and Deep Learning Techniques. 10. Intelligent Diagnosis Support System for Screening Diabetes Subjects using Hybrid Machine Learning Algorithms. 11. Cyber-Physical System for Managing Diabetic Health Care.