Self-Learning AI in Healthcare

Dr. Rajesh Kumar Dhanaraj is a professor at the Symbiosis International (Deemed University) in Pune, India. His research and publication interests include cyber-physical systems, wireless sensor networks, and cloud computing. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a member of the Computer Science Teacher Association (CSTA) and member of the International Association of Engineers (IAENG). He is an expert advisory panel member of Texas Instruments Inc. (USA), and an associate editor of International Journal of Pervasive Computing and Communications (Emerald Publishing). Dr. M. Sangeetha is an Assistant Professor (SLG) in the Department of Computer Science and Engineering, PSG Institute of Technology and Applied Research, Coimbatore, Tamil Nadu, India. She received her M.E. degree in Computer Science and Engineering from Anna University, India, in 2010. She completed her Ph.D. in Information and Communication Engineering from Anna University, Chennai, India, in 2024.She is a life member of the Computer Society of India (CSI). Dr. Sangeetha has published more than 20 research papers in high-quality SCI impact factor journals indexed in Scopus and ESCI, 24 papers in international conferences indexed by Springer and IEEE Xplore, and holds one patent. Dr. R. Manjula Devi received her B.E. and M.E. degrees in Computer Science and Engineering in 2004 and 2006, respectively, from Bharathiyar University, Coimbatore, and Anna University, Chennai. She earned her Ph.D. degree in Information and Communication Engineering, specializing in Neural Networks, from Anna University, Chennai, in 2015.She is currently a Professor in the Department of Computer Science and Engineering at KPR Institute of Engineering and Technology, Coimbatore. She has received numerous prestigious awards, including the Best Faculty Award in CSE, Shri P.K. Das Memorial Best Faculty Award, Best Author Award, Best Young Teacher Award, and the Dr. A.P.J. Abdul Kalam Award, among others, from various organizations.She is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and a member of the Computer Society of India. She also serves as a reviewer for various journals and conferences. Her research interests include Soft Computing, Pattern Classification and Recognition, Internet of Things, and Image Processing.Mahmoud Ahmad Al-Khasawneh is a faculty member in the School of Computing Skyline University College, Sharjah UAE.His scholarly pursuits span a diverse array of fields within computer science. He has authored numerous papers in esteemed, peer-reviewed journals across leading publishers such as IEEE, Springer, Wiley, Hindawi, and MDPI. His research interests encompass Security, Image Encryption, Wireless Networks, Blockchain, Internet of Things, and Big Data. With a commitment to advancing knowledge and solving contemporary challenges in these domains, he actively engages in research, teaching, and mentorship, contributing to the academic and professional development of his students and peers. Driven by a passion for innovation and a dedication to excellence, he continues to make significant contributions to the field, shaping the future of technology and its applications. Dr. Firoz Khan is an Assistant Professor at Ball State University’s Center for Information and Communication Sciences. His research focuses on securing systems under attack, with particular emphasis on network security, information assurance, and cybersecurity. He also investigates the application of machine learning techniques for data analysis and big data challenges.Dr. Khan is dedicated to educating students in computer and network security, ethical hacking, digital forensics, and the integration of machine learning with cybersecurity issues. His scholarly work has been widely recognized, with over 850 citations highlighting his significant impact in the field.

• 1. The Rise of Self-Learning AI in Healthcare: A New Era of Intelligent Medicine2. Neural Networks and Deep Learning for Self-Adaptive Medical Systems3. Unsupervised and Semi-Supervised Learning for Medical Data Analysis4. Reinforcement Learning for Autonomous Decision-Making in Healthcare5. Edge AI and On-Device Learning for Decentralized Healthcare Systems6. Personalized Medicine with Self-Learning AI for Treatment Optimization7. Hospital Workflow Optimization with Self-Learning AI8. Self-Learning Powered Remote Patient Monitoring and Real-Time Adaptation9. Self-Learning AI for Early Disease Detection and Preventive Medicine10. Federated Learning for Privacy-Preserving Self-Learning AI in Healthcare11. AI-Driven Personalized Rehabilitation and Adaptive Therapy12. Self-Learning AI for Drug Discovery and Development Acceleration13. Self-Improving AI for Mental Health Support and Cognitive Therapy14. Autonomous AI for Personalized Treatment Plans15. Adaptive AI in Radiology: Real-Time Image Interpretation and Diagnosis16. Digital Twins in Healthcare: Self-Learning AI for Predictive and Preventive Medicine17. Self-Learning AI for Medical Robotics: Towards Autonomous Surgical and Assistive Systems18. The Future of Self-Learning AI in Healthcare: Challenges, Ethics, and Regulatory Considerations