Poonam Rawat
Papers
2
Total Citations
6
H-Index
2
About
Poonam Rawat is a rising researcher at the intersection of artificial intelligence and healthcare, with a focus on optimizing critical medical processes through machine learning. Her most notable contribution, "The Role of Artificial Intelligence in Optimizing the Donation Process and Predicting Blood Thresholds" (2023), which has garnered 4 citations, introduces innovative AI-driven approaches to improve blood donation efficiency and predict supply-demand gaps—a vital step toward smarter healthcare logistics. In parallel, her work "Recognition of Handwritten Digits Using Convolutional Neural Network in Python and Comparison of Performance for Various Hidden Layers" (2023, 2 citations) demonstrates her technical depth in deep learning, systematically evaluating CNN architectures to enhance pattern recognition accuracy. Rawat’s research bridges practical healthcare challenges with robust computational methods, offering scalable solutions for real-world applications. Her early citation impact signals growing recognition in the AI and medical informatics communities. For students and researchers exploring how AI can transform operational healthcare, Rawat’s work provides a clear, actionable blueprint for integrating predictive analytics into life-saving processes.
Research Focus
Key Achievements
Top Papers
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- 2