Senthil K. Nachimuthu

Senthil K. Nachimuthu, MD, PhD, FAMIA

Languages spoken: English

Academic Information

Departments Primary - Internal Medicine , Adjunct - Biomedical Informatics

Divisions: Epidemiology

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
Professional Medical Stanley Medical College
 MBBS

Selected Publications

Journal Article

  1. Peterson KS, Dalton C, Kalvesmaki A, Vuong J, Gordon C, Nachimuthu S, Pugh MJ, Jones MM (2026). Identifying Early Signals From Emerging Public Health Events Using Natural Language Processing. Interdiscip Perspect Infect Dis, 2026, 6176855.
  2. 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.
  3. Gupta A, Lash MT, Nachimuthu SK (2021). Optimal Sepsis Patient Treatment using Human- in-the-loop Artificial Intelligence. Expert Syst Appl, 169(114476).
  4. Nachimuthu SK, Lau LM (2007). Practical issues in using SNOMED CT as a reference terminology. Stud Health Technol Inform, 129(Pt 1), 640-4.

Book Chapter

  1. Cummins MR, Nachimuthu SK, Abdelrahman SE, Facelli JC, Gouripeddi R (2023). Nonhypothesis-driven research: data mining and knowledge discovery. In Clinical Research Informatics (Health Informatics) (pp. 413-32). Springer International Publishing.

Conference Proceedings

  1. John O, Nachimuthu SK, Veil KD, Gogia SB, Jha V (2016). Informatics Beyond Boundaries: An Experience of Technology Enabled Remote Support in Natural Disasters – Nepal Earthquake 2015 Relief Portal. Proceedings of the 2016 Conference of Asia Pacific Association for Medical Informatics.
  2. Nachimuthu SK, Lau LM (2015). HDD Access – An Open Source Terminology Server with Publicly Available Terminology Content. American Medical Informatics Association Annual Symposium Proceedings.
  3. Howe R, Kartchner T, Humpherys K, Harman T, Matney SA, Nachimuthu SK (2014). Evaluation of SNOMED CT Content Coverage for a Decision Support System. American Medical Informatics Association Annual Symposium Proceedings.
  4. Totzke M, Nachimuthu SK (2013). Mapping HL7 CVX codes to RxNorm RXCUIs. American Medical Informatics Association Annual Symposium Proceedings.
  5. Nachimuthu SK, Haug PJ (2012). Early Detection of Sepsis in the Emergency Department using Dynamic Bayesian Networks. American Medical Informatics Association Annual Symposium Proceedings.
  6. Wong A, Nachimuthu SK, Haug PJ (2012). Predicting Readmissions among Heart Failure Patients using Dynamic Bayesian Network. American Medical Informatics Association Annual Symposium Proceedings.
  7. Nachimuthu SK, Wong A, Haug PJ (2010). Modeling Glucose Homeostasis and Insulin Dosing in an Intensive Care Unit using Dynamic Bayesian Networks. American Medical Informatics Association Annual Symposium Proceedings.
  8. Nachimuthu SK, Davis TC, Yendt CM (2010). Lessons from an Open-Source Implementation of HL7 Common Terminology Services through an Industry – Academia Partnership. American Medical Informatics Association Annual Symposium Proceedings.
  9. He S, Nachimuthu SK, Shakib SC, Lau LM (2009). Collaborative Authoring of Biomedical Terminologies with Semantic Wiki. American Medical Informatics Association Annual Symposium Proceedings.

Abstract

  1. Seshachalam A, Anandan KN, Dharaniraj T, Jenitha E, Kumarappan S, Kumar A, Shankar K, Maskomani S, Nachimuthu SK, Mohan SP, Krishnamoorthi N, Chandralekha K, Saju SV, Ganeshprasad A (2026). The AI paradox in precision oncology: Prospective blinded validation of large language models against molecular tumor board [Abstract]. 44(16).