Dr. Betshrine Rachel | Federated Learning | Chemistry | Best Researcher Award
Anna University, India
A Ph.D. graduate in Computer Science and Engineering, the researcher specializes in AI-driven medical imaging and disease diagnosis. Academic training includes undergraduate, postgraduate, and doctoral studies in computing disciplines. Professional experience spans teaching, research mentorship, and development of intelligent diagnostic systems. Research focuses on deep learning, evolutionary optimization, federated learning, radiomics, and privacy-preserving AI for healthcare applications such as pulmonary disorders and sepsis prediction. Recognized through academic excellence and research contributions, the work emphasizes ethical, scalable, and clinically impactful AI solutions advancing interdisciplinary healthcare innovation.
Total Citations
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Featured Publications
Diagnosis of COVID-19 from CT slices using whale optimization algorithm, support vector machine and multi-layer perceptron
– Journal of X-Ray Science and Technology · Cited by 18
Diagnosis of Pulmonary Edema and COVID-19 from CT slices using squirrel search algorithm, SVM and back propagation neural network
– Journal of Intelligent & Fuzzy Systems · Cited by 18
Diagnosis of COVID-19 from computed tomography slices using flower pollination algorithm, k-nearest neighbor, and SVM classifiers
– Artificial Intelligence in Health · Cited by 12
FL-WOSP: Federated Learning with Walrus Optimization for Sepsis Prediction Using MIMIC-III Physiological and Clinical Data
– Pattern Recognition (Elsevier) · Cited by 1
Systematic review of privacy-preserving Federated Learning in decentralized healthcare systems
– Franklin Open (Elsevier) · Cited by 1