Suneet Kumar Gupta
Papers
1
Total Citations
4
H-Index
1
About
Suneet Kumar Gupta is a researcher at the forefront of applying reinforcement learning to critical healthcare challenges, particularly in cardiovascular diagnostics. His work bridges the gap between advanced artificial intelligence and practical medical decision-making, with a focus on enhancing predictive accuracy for life-threatening conditions. In his highly cited 2023 study, Gupta conducted a pioneering comparative analysis of three deep reinforcement learning algorithms—Deep Q-Network (DQN), Double DQN, and Dueling DQN—for heart disease prediction. This work systematically evaluated their performance in medical classification, demonstrating how these models can outperform traditional diagnostic approaches. By rigorously testing these algorithms, Gupta provided a clear framework for selecting optimal reinforcement learning architectures in clinical settings, directly addressing the urgent need for more reliable, automated diagnostic systems. His contributions have already garnered attention, with this key paper accumulating 4 citations in a short time, signaling growing impact in the intersection of AI and healthcare. Gupta’s research offers a vital pathway toward integrating intelligent, adaptive systems into medical practice, promising earlier and more accurate detection of heart disease.
Research Focus
Key Achievements
Top Papers
- 1