Deepak Ranjan Nayak
Papers
2
Total Citations
107
H-Index
2
About
Deepak Ranjan Nayak is a leading researcher in biomedical image analysis and computational intelligence, with a primary focus on developing automated systems for brain pathology detection. His work bridges machine learning, signal processing, and medical diagnostics, particularly through the application of advanced feature extraction and optimization algorithms. Nayak’s most cited contributions include a 2018 study that combines extreme learning machines with a modified sine cosine algorithm for pathological brain detection, achieving 54 citations, and a 2017 paper introducing a fast discrete curvelet transform and probabilistic neural network approach for the same task, cited 53 times. These studies have significantly advanced the accuracy and efficiency of computer-aided diagnosis for brain disorders, offering robust alternatives to traditional manual analysis. His research is notable for its innovative integration of nature-inspired optimization techniques with neural networks, setting benchmarks for automated medical imaging systems. With over 100 cumulative citations, Nayak’s work continues to influence the fields of biomedical engineering and artificial intelligence, providing scalable solutions for early and reliable detection of pathological conditions.
Research Focus
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Top Papers
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