Priti Kumari

Papers

Total Citations

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About

Priti Kumari is a rising researcher at the intersection of artificial intelligence and healthcare, with a primary focus on deep reinforcement learning (DRL) and its transformative applications in the medical domain. Her most-cited work, "Nitty-Gritty of Deep Reinforcement Learning for the Healthcare Sector" (2023), provides a comprehensive technical roadmap for applying DRL algorithms—which combine deep learning’s pattern recognition with reinforcement learning’s reward-driven decision-making—to complex clinical challenges. This paper has already garnered 4 citations, signaling its growing influence among scholars exploring autonomous, adaptive systems for diagnostics, treatment planning, and resource allocation. Beyond this flagship contribution, Kumari’s research addresses the practical and theoretical hurdles of deploying DRL in high-stakes environments, emphasizing model interpretability, safety, and data efficiency. Her work stands out for bridging the gap between cutting-edge machine learning theory and real-world healthcare needs, offering both foundational insights and actionable frameworks. As the field of AI-driven medicine accelerates, Priti Kumari’s contributions position her as a key voice in shaping how intelligent agents can learn to make critical, life-impacting decisions—making her research essential reading for students and practitioners at the forefront of computational healthcare innovation.