Deepika Pantola
Papers
2
Total Citations
22
H-Index
2
About
Deepika Pantola is a rising researcher at the forefront of artificial intelligence and its medical applications, with a primary focus on neural network architectures and reinforcement learning. Her work bridges the gap between theoretical model development and practical healthcare solutions. In her highly cited 2024 survey, "Neural network developments: A detailed survey from static to dynamic models," Pantola provides a comprehensive roadmap of evolving AI architectures, establishing a foundational reference for researchers navigating the transition from traditional to adaptive neural systems. Demonstrating the translational impact of her work, she applies advanced reinforcement learning to critical healthcare challenges. Her 2023 study, "Performance Evaluation of DQN, DDQN and Dueling DQN in Heart Disease Prediction," conducts a rigorous comparative analysis of deep Q-network variants for medical diagnosis. This work directly addresses the global burden of heart disease by evaluating which algorithmic approach yields the most accurate diagnostic systems. Through this targeted application, Pantola showcases how state-of-the-art AI techniques can be harnessed to improve clinical decision-making, marking her as a promising contributor to the intersection of deep learning and precision medicine.
Research Focus
Key Achievements
Top Papers
- 1Neural network developments: A detailed survey from static to dynamic models18 citations · 2024
- 2