Supervised Learning Models for the Preliminary Detection of COVID-19 in Patients Using Demographic and Epidemiological Parameters. - Aditya Pradhan; Srikanth Prabhu; Krishnaraj Chadaga; Saptarshi Sengupta; Gopal Nath (Inf., 2022)

Diagnosing COVID-19 using artificial intelligence: a comprehensive review. - Varada Vivek Khanna; Krishnaraj Chadaga; Niranjana Sampathila; Srikanth Prabhu; Rajagopala Chadaga; Shashikiran Umakanth (Netw. Model. Anal. Health Informatics Bioinform., 2022)

Classification of Malaria Using Object Detection Models. - Padmini Krishnadas; Krishnaraj Chadaga; Niranjana Sampathila; Santhosha Rao; Swathi Katta S.; Srikanth Prabhu (Informatics, 2022)

Severity prediction in COVID-19 patients using clinical markers and explainable artificial intelligence: A stacked ensemble machine learning approach. - Krishnaraj Chadaga; Srikanth Prabhu; Niranjana Sampathila; Rajagopala Chadaga (Intell. Decis. Technol., 2023)

Multiple Explainable Approaches to Predict the Risk of Stroke Using Artificial Intelligence. - Susmita S.; Krishnaraj Chadaga; Niranjana Sampathila; Srikanth Prabhu; Rajagopala Chadaga; Swathi Katta S. (Inf., 2023)

Channel Intensity and Edge-Based Estimation of Heart Rate via Smartphone Recordings. - Anusha Krishnamoorthy; Giliyar Muralidhar Bairy; Siddeshappa Nandish; Hilda Mayrose; Niranjana Sampathila; Krishnaraj Chadaga (Comput., 2023)

Classification of Surya Namaskar Yoga Asanas: A Sequential Combination of Predominant Poses for Physical and Mental Health. - Venkatesh A. Bhandage; Srikanth Prabhu; Balachandra S. Hadimani; Krishnaraj Chadaga; Niranjana Sampathila; Sucharitha Shetty (IEEE Access, 2024)

An Explainable Decision Support Framework for Differential Diagnosis Between Mild COVID-19 and Other Similar Influenzas. - Krishnaraj Chadaga; Srikanth Prabhu; Niranjana Sampathila; Rajagopala Chadaga; Shashikiran Umakanth (IEEE Access, 2024)

Using Explainable Machine Learning Methods to Predict the Survivability Rate of Pediatric Respiratory Diseases. - Roshan Kumar; V. Srirama; Krishnaraj Chadaga; H. Muralikrishna; Niranjana Sampathila; Srikanth Prabhu; Rajagopala Chadaga (IEEE Access, 2024)

Empowering Glioma Prognosis With Transparent Machine Learning and Interpretative Insights Using Explainable AI. - Anisha Palkar; Cifha Crecil Dias; Krishnaraj Chadaga; Niranjana Sampathila (IEEE Access, 2024)

Digital Pathology in Healthcare: Current Trends and Future Perspective. - Neelankit Gautam Goswami; Niranjana Sampathila; Giliyar Muralidhar Bairy; Krishnaraj Chadaga; Anushree Goswami; Sushma Belurkar (Int. J. Online Biomed. Eng., 2024)

Wavelet scattering- and object detection-based computer vision for identifying dengue from peripheral blood microscopy. - Liora Rosvin Dsilva; Shivani Harish Tantri; Niranjana Sampathila; Hilda Mayrose; Giliyar Muralidhar Bairy; Sushma Belurkar; Kavitha Saravu; Krishnaraj Chadaga; Abdul Hafeez-Baig (Int. J. Imaging Syst. Technol., 2024)

Demystifying multiple sclerosis diagnosis using interpretable and understandable artificial intelligence. - Krishnaraj Chadaga; Varada Vivek Khanna; Srikanth Prabhu; Niranjana Sampathila; Rajagopala Chadaga; Anisha Palkar (J. Intell. Syst., 2024)

Detection of sickle cell disease using deep neural networks and explainable artificial intelligence. - Neelankit Gautam Goswami; Anushree Goswami; Niranjana Sampathila; Giliyar Muralidhar Bairy; Krishnaraj Chadaga; Sushma Belurkar (J. Intell. Syst., 2024)

Ischemic Heart Disease Prognosis: A Hybrid Residual Attention-Enhanced LSTM Model. - D. Cenitta; R. Vijaya Arjunan; Ganesh Paramasivam; N. Arul; Anisha Palkar; Krishnaraj Chadaga (IEEE Access, 2025)

Cardiac Clarity: Harnessing Machine Learning for Accurate Heart-Disease Prediction. - Sujith Santhosh; Krishnaraj Chadaga; R. Vijaya Arjunan; Sandra D'Souza (IEEE Access, 2025)