Sonam Khattar
Papers
1
Total Citations
3
H-Index
1
About
Sonam Khattar is a rising researcher in biomedical informatics and machine learning, whose work focuses on improving the early detection and diagnosis of cardiovascular disease. Her most-cited study, "An Empirical Study of Machine Learning Methods for Analyzing Cardiovascular Disease" (2023), directly addresses the critical need for safer, more accessible diagnostic tools. Khattar’s research confronts the limitations of conventional procedures like angiography, which are costly and carry significant health risks. By systematically evaluating various machine learning algorithms on clinical datasets, she demonstrates how predictive models can leverage routine patient data to identify heart disease risk with high accuracy. This work not only highlights the potential of AI to reduce reliance on invasive testing but also provides a practical framework for integrating data-driven methods into clinical workflows. With her paper already garnering early citations, Khattar is establishing herself as a contributor to the growing field of computational cardiology. Her research is particularly valuable for students and practitioners seeking to understand how machine learning can transform patient outcomes by making cardiovascular screening more efficient, affordable, and safe.
Research Focus
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Top Papers
- 1