Assistant Professor | GLA University | India
Assist. Prof. Dr. Law Kumar Singh is a distinguished researcher whose scientific contributions have significantly shaped advancements in Medical Image Processing, artificial intelligence, and clinical decision-support systems. His work demonstrates a consistent commitment to enhancing healthcare diagnostics through Medical Image Processing, with notable achievements in breast cancer prediction, glaucoma detection, diabetic retinopathy assessment, and automated medical screening technologies. Recognized for integrating nature-inspired algorithms with deep learning, he has established a strong research presence built upon innovation and high-impact publications in Medical Image Processing. Throughout his career, Assist. Prof. Dr. Law Kumar Singh has authored influential studies that advance Medical Image Processing by developing hybrid architectures, robust optimization frameworks, and deep neural network models tailored for medical applications. His collaborations with leading experts across computer vision, machine learning, and biomedical engineering have strengthened the translational impact of Medical Image Processing, ensuring that his research contributes both to academic progress and clinical relevance. He has produced numerous widely cited works, reflecting the global recognition of his contributions to Medical Image Processing. His research portfolio highlights a strong focus on real-world medical challenges, where Medical Image Processing serves as a transformative tool for early disease identification and improved patient outcomes. By blending algorithmic efficiency with diagnostic precision, he has consistently demonstrated how Medical Image Processing can elevate the accuracy and reliability of automated healthcare systems. His collaborative projects further emphasize interdisciplinary integration, reinforcing the essential role of Medical Image Processing in solving complex biomedical problems. Assist. Prof. Dr. Law Kumar Singh continues to expand the frontiers of Medical Image Processing through rigorous research, impactful publications, and sustained contributions to global scientific communities. His work stands as a benchmark for excellence in data-driven healthcare innovation. Google Scholar profile of 1558 Citations, 27 h-index, 36 i10-index.
Profile: Google Scholar
Featured Publications
1. Thawkar, S., Sharma, S., Khanna, M., & Singh, L. K. (2021). Breast cancer prediction using a hybrid method based on butterfly optimization algorithm and ant lion optimizer. Computers in Biology and Medicine, 139, 104968.
2. Singh, L. K., Khanna, M., & Singh, R. (2023). Artificial intelligence based medical decision support system for early and accurate breast cancer prediction. Advances in Engineering Software, 175, 103338.
3. Singh, L. K., Pooja, Garg, H., Khanna, M., & Bhadoria, R. S. (2021). An enhanced deep image model for glaucoma diagnosis using feature-based detection in retinal fundus. Medical & Biological Engineering & Computing, 59(2), 333–353.
4. Khanna, M., Singh, L. K., Thawkar, S., & Goyal, M. (2024). PlaNet: A robust deep convolutional neural network model for plant leaves disease recognition. Multimedia Tools and Applications, 83(2), 4465–4517.
5. Singh, L. K., Pooja, Garg, H., & Khanna, M. (2022). Deep learning system applicability for rapid glaucoma prediction from fundus images across various data sets. Evolving Systems, 13(6), 807–836.