Charanjeet Gaba
Papers
2
Total Citations
5
H-Index
2
About
Charanjeet Gaba is a rising researcher at the intersection of machine learning and healthcare, with a focused expertise in predictive analytics for cardiovascular disease. His work addresses a critical public health challenge: the high cost and invasive nature of traditional diagnostic procedures like angiography. Gaba’s major contributions lie in developing and empirically validating machine learning frameworks that can analyze patient data to predict heart disease risk more safely and affordably. His 2023 study, "An Empirical Study of Machine Learning Methods for Analyzing Cardiovascular Disease," has garnered 3 citations, establishing a foundation for non-invasive diagnostic alternatives. Building on this, his 2024 paper, "Machine Learning Method for Analyzing and Predicting Cardiovascular Disease," advances the field with refined predictive models, earning 2 citations. Though early in his career, Gaba’s work is notable for its direct translational potential—aiming to reduce the risks and costs associated with conventional heart disease screening. His research promises to democratize cardiovascular diagnostics, making early detection accessible through data-driven approaches. For students and researchers, Gaba exemplifies how machine learning can be harnessed for impactful, life-saving medical applications.
Research Focus
Key Achievements
Top Papers
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- 2