Senthil Nachimuthu is a Research Assistant Professor of Epidemiology and an Adjunct Assistant Professor of Biomedical Informatics at the School of Medicine. His research involves creating and validating machine learning methods in healthcare, and applying them to infectious disease epidemiology and other clinical areas. Before his academic role, he worked for more than 15 years in the industry in research and leadership roles in data standardization, interoperability, multimodal artificial intelligence, and open data.
During his industry career, Dr. Nachimuthu advised a US Congressional Committee to improve interoperability of medical records between the VA and DoD, and he served an elected US representative on the SNOMED Technical Committee. Senthil likes to leverage his academic and industry experience to ensure that his research will be implementable at the bedside and the implementations will be supported by scientific evidence.
Senthil's research at the Salt Lake City VA Medical Center and the University of Utah School of Medicine involves multimodal and responsible machine learning, and infectious disease epidemiology. His teaching interests include biomedical terminologies, interoperability standards, and clinical decision support.
Senthil received his medical degree from Stanley Medical College, Chennai, India and his PhD in Biomedical Informatics from the University of Utah School of Medicine. He has been inducted as a Fellow of the American Medical Informatics Association.
Education History
Doctoral Training |
University of Utah School of Medicine |
PhD |
---|---|---|
Stanley Medical College |
MBBS |
Selected Publications
Journal Article
- Smits PD, Gratzl S, Simonov M, Nachimuthu SK, Goodwin Cartwright BM, Wang MD, Baker C, Rodriguez P, Bogiages M, Althouse BM, Stucky NL (2023). Risk of COVID-19 breakthrough infection and hospitalization in individuals with comorbidities. Vaccine, 41(15), 2447-2455. (Read full article)
- Nachimuthu SK, Lau LM (2007). Practical issues in using SNOMED CT as a reference terminology. Stud Health Technol Inform, 129(Pt 1), 640-4. (Read full article)