Varada Khanna, MSPH

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About

Second Year PhD Student in Biomedical Informatics and Data Science

Supervisor: Hua Xu, PhD, Robert T. McCluskey Professor of Biomedical Informatics and Data Science

Last Updated on June 20, 2026.

BTech: Manipal Academy of Higher Education, Biomedical Engineering (Minor: Computational Mathematics) (2023)

Frequent collaborators of Varada Khanna's published research.

Electronic health record use factors linked to efficiency and productivity: an explainable machine learning analysis
Li H, Khanna V, Apathy N, Holmgren A, Loza A, Melnick E. Electronic health record use factors linked to efficiency and productivity: an explainable machine learning analysis. JAMIA Open 2026, 9: ooag018. PMID: 41767181, PMCID: PMC12936052, DOI: 10.1093/jamiaopen/ooag018.
Peer-Reviewed Original Research
This study investigates electronic health record (EHR) use patterns among physicians, showing that timely inbox management and reduced after-hours work improve chart completion efficiency and patient visit volume.
Full Summary

Author Correction: An interpretable and transparent machine learning framework for appendicitis detection in pediatric patients
Chadaga K, Khanna V, Prabhu S, Sampathila N, Chadaga R, Umakanth S, Bhat D, Swathi K, Kamath R. Author Correction: An interpretable and transparent machine learning framework for appendicitis detection in pediatric patients. Scientific Reports 2025, 15: 2841. PMID: 39843648, PMCID: PMC11754466, DOI: 10.1038/s41598-025-86494-x.
Commentaries, Editorials and Letters

An interpretable and transparent machine learning framework for appendicitis detection in pediatric patients
Chadaga K, Khanna V, Prabhu S, Sampathila N, Chadaga R, Umakanth S, Bhat D, Swathi K, Kamath R. An interpretable and transparent machine learning framework for appendicitis detection in pediatric patients. Scientific Reports 2024, 14: 24454. PMID: 39424647, PMCID: PMC11489819, DOI: 10.1038/s41598-024-75896-y.
Peer-Reviewed Original Research
MeSH Keywords
Explainable artificial intelligence-driven gestational diabetes mellitus prediction using clinical and laboratory markers
Vivek Khanna V, Chadaga K, Sampathila N, Prabhu S, Chadaga P. R, Bhat D, K. S. S. Explainable artificial intelligence-driven gestational diabetes mellitus prediction using clinical and laboratory markers. Cogent Engineering 2024, 11: 2330266. DOI: 10.1080/23311916.2024.2330266.
Peer-Reviewed Original Research
Demystifying multiple sclerosis diagnosis using interpretable and understandable artificial intelligence
Chadaga K, Khanna V, Prabhu S, Sampathila N, Chadaga R, Palkar A. Demystifying multiple sclerosis diagnosis using interpretable and understandable artificial intelligence. Journal Of Intelligent Systems 2024, 33: 20240077. DOI: 10.1515/jisys-2024-0077.
Peer-Reviewed Original Research

A decision support system for osteoporosis risk prediction using machine learning and explainable artificial intelligence
Khanna V, Chadaga K, Sampathila N, Chadaga R, Prabhu S, K S S, Jagdale A, Bhat D. A decision support system for osteoporosis risk prediction using machine learning and explainable artificial intelligence. Heliyon 2023, 9: e22456. PMID: 38144333, PMCID: PMC10746430, DOI: 10.1016/j.heliyon.2023.e22456.
Peer-Reviewed Original Research
A machine learning and explainable artificial intelligence triage-prediction system for COVID-19
Khanna V, Chadaga K, Sampathila N, Prabhu S, P. R. A machine learning and explainable artificial intelligence triage-prediction system for COVID-19. Decision Analytics Journal 2023, 7: 100246. PMCID: PMC10163946, DOI: 10.1016/j.dajour.2023.100246.
Peer-Reviewed Original Research
A Distinctive Explainable Machine Learning Framework for Detection of Polycystic Ovary Syndrome
Khanna V, Chadaga K, Sampathila N, Prabhu S, Bhandage V, Hegde G. A Distinctive Explainable Machine Learning Framework for Detection of Polycystic Ovary Syndrome. Applied System Innovation 2023, 6: 32. DOI: 10.3390/asi6020032.
Peer-Reviewed Original Research

Diagnosing COVID-19 using artificial intelligence: a comprehensive review
Khanna V, Chadaga K, Sampathila N, Prabhu S, Chadaga R, Umakanth S. Diagnosing COVID-19 using artificial intelligence: a comprehensive review. Network Modeling Analysis In Health Informatics And Bioinformatics 2022, 11: 25. DOI: 10.1007/s13721-022-00367-1.
Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements