Papers
2
Total Citations
91
H-Index
2
About
Dr. R. Udendhran is a researcher whose work sits at the intersection of machine learning, medical diagnostics, and cloud robotics. Their most impactful contribution is a hybridized neural network and decision tree classifier for prognostic decision-making in breast cancers, a 2019 study that has garnered 89 citations and demonstrates a practical application of AI in improving clinical outcomes. This work underscores their focus on developing interpretable, hybrid models that balance predictive power with clinical utility. Although a 2023 paper on explainable fuzzy convolutional autoencoders for cloud robotic vision was retracted, the core interest in explainable AI and representation learning remains evident. Dr. Udendhran’s research is notable for bridging the gap between advanced computational methods and real-world healthcare challenges, offering tools that could assist pathologists and oncologists in making more accurate, data-driven decisions. Their work continues to influence the growing field of AI-assisted diagnostics.
Research Focus
Key Achievements
Top Papers
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