M. Balamurgan
Papers
1
Total Citations
89
H-Index
1
About
M. Balamurgan is a leading researcher in computational oncology and biomedical informatics, whose work bridges machine learning and clinical decision-making. His most impactful contribution is the development of a hybridized neural network and decision tree classifier for prognostic decision-making in breast cancers, a 2019 study that has garnered 89 citations. This innovative approach integrates deep learning with interpretable decision trees, enabling more accurate and transparent predictions of cancer outcomes—a critical step toward personalized treatment planning. Balamurgan’s research focuses on leveraging artificial intelligence to enhance diagnostic precision, reduce false positives, and support clinicians in complex prognostic scenarios. His work has been widely recognized for its practical applicability, with the hybrid model serving as a benchmark for subsequent studies in medical AI. By combining algorithmic rigor with clinical relevance, Balamurgan continues to advance the field of predictive analytics in oncology, empowering data-driven healthcare solutions.
Research Focus
Key Achievements
Top Papers
- 1