Fenil Ramoliya
Papers
1
Total Citations
4
H-Index
1
About
Fenil Ramoliya is a researcher at the forefront of cybersecurity and explainable artificial intelligence, with a particular focus on safeguarding critical infrastructures in the healthcare domain. His work addresses the pressing security challenges of Healthcare 4.0, where the integration of Medical Internet of Things (MIoT), patient-centric devices, and remote robotic systems has blurred the lines between physical and virtual care. Ramoliya’s most cited paper, “X-NET: Explainable AI-Based Network Data Security Framework for Healthcare 4.0” (2024), introduces a novel framework that not only detects network threats but also provides transparent, interpretable insights into its decision-making—a crucial step for building trust in AI-driven medical systems. This work has already garnered 4 citations, signaling its early influence in the field. By combining explainability with robust security, Ramoliya’s contributions help ensure that remote patient monitoring and other telehealth innovations remain both effective and resilient against cyberattacks. His research is particularly valuable for students and practitioners seeking to understand how AI can be ethically and securely deployed in high-stakes healthcare environments.
Research Focus
Key Achievements
Top Papers
- 1