Kayvan Najarian, PhD
Professor of Computational Medicine and Bioinformatics
Professor of Emergency Medicine
Professor of Electrical Engineering and Computer Science
[email protected]

Available to mentor

Kayvan Najarian, PhD
Professor
  • About
  • Links
  • Center Memberships
  • Research Overview
  • Recent Publications
  • About

    Dr. Kayvan Najarian is a Professor in the Gilbert S. Omenn Department of Computational Medicine and Bioinformatics (DCMB) as well as the departments of Emergency Medicine and Electrical Engineering and Computer Science at the University of Michigan. He is the Director of the Biomedical and Clinical Informatics Laboratory (BCIL) and is an Associate Director for the Weil Institute for Critical Care Research and Innovation. Dr. Najarian is also an Associate Director for the Michigan Institute for Data Science (MIDAS), serving as the point person for data science collaboration in Biological Sciences and Health Sciences.

    Dr. Najarian received his Ph.D. in Electrical and Computer Engineering from University of British Columbia, Canada, M.Sc in Biomedical Engineering from Amirkabir University, Iran, and B.Sc. in Electrical Engineering from Sharif University, Iran. The focus of Dr. Kayvan Najarian’s research is on the design of signal/image processing and machine learning methods to create computer-assisted clinical decision support systems that improve patient care and reduce the costs of healthcare.

    Dr. Najarian’s lab also designs sensors to collect and analyze physiological signals and images. In particular, Dr. Najarian’s research focuses on creating decision support systems to manage traumatic brain injuries, traumatic pelvic/abdominal injuries and hemorrhagic shock, cardiac arrest and other critical care states.

    Dr. Najarian’s research has been funded by agencies such as the National Science Foundation, the National Institutes of Health, and the Department of Defense. He serves as the Editor-in-Chief of Biomedical Engineering and Computational Biology and the Associate Editor of two other journals in the field of biomedical informatics. He is also a member of the editorial board of many other journals and serves as the guest editor of special issues for several journals in the field. Dr. Najarian has over 200 peer-reviewed journal and conference publications including a highly referenced textbook in the field of biomedical signal and image processing.

    Links
    • Najarian Lab
    Center Memberships
    • Center Member
      Center for Integrative Research in Critical Care
    • Center Member
      Institute for Healthcare Policy and Innovation
    • Center Member
      Caswell Diabetes Institute
    • Center Member
      e-Health and Artificial Intelligence Initiative
    Research Overview

    Dr. Najarian, as the director of the Biomedical and Clinical Informatics Lab at the University of Michigan, is a distinguished researcher in the field of computational medicine, with a primary focus on leveraging artificial intelligence (AI) and machine learning (ML) for medical applications through clinical decision support systems and drug discovery and assessment. Resulting AI-based technologies for clinical decision support systems, which have been funded by agencies such as NSF, NIH, and DoD, feature advanced signal/image processing and ML techniques. In addition, he has collaborated with industry giants including J&J, BMS, and Toyota aimed at developing AI-based medical decision support systems for cardiovascular and gastrointestinal diseases. The success of these endeavors is evident in the licensing of these technologies to private companies, highlighting the real-world impact in advancing healthcare through computational medicine. Dr. Najarian is an Associate Director of the Michigan Institute for Data Science (MIDAS), focusing specifically on the integration of AI in healthcare and an Associate Director of the Weil Institute where he directs efforts toward AI applications in critical care. These roles signify Dr. Najarian’s commitment to driving innovation and improving patient outcomes through the implementation of cutting-edge AI technologies. Furthermore, as the Director of the Center for Data-Driven Drug Development and Treatment Assessment (DATA), an NSF IUCRC, Dr. Najarian coordinates all activities in this national center towards advancing the frontier of AI in drug development and contributes significantly to research in this field.

    Recent Publications See All Publications
    • Journal Article
      Continuous sepsis trajectory prediction using tensor-reduced physiological signals.
      Alge OP, Pickard J, Zhang W, Cheng S, Derksen H, Omenn GS, Gryak J, VanEpps JS, Najarian K. Sci Rep, 2024 Aug 6; 14 (1): 18155 DOI:10.1038/s41598-024-68901-x
      PMID: 39103488
    • Journal Article
      Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.
      Zhang Y, Golbus JR, Wittrup E, Aaronson KD, Najarian K. BMC Med Inform Decis Mak, 2024 Feb 14; 24 (1): 53 DOI:10.1186/s12911-024-02453-y
      PMID: 38355512
    • Journal Article
      Identifying selective PDHK inhibitors using coupled tensor matrix completion and experimental validation
      Rajaei F, Toogood P, Jacob R, Baber M, Gough M, Derksen H, Wittrup E, Najarian K. Discover Artificial Intelligence, 2024 Dec 1; 4 (1): DOI:10.1007/s44163-024-00202-8
    • Preprint
      Identification of Digital Twins to Guide Interpretable AI for Diagnosis and Prognosis in Heart Failure
      Gu F, Meyer AJ, Ježek F, Zhang S, Catalan T, Miller A, Schenk N, Sturgess V, Uceda D, Li R, Wittrup E, Hua X, Carlson BE, Tang Y-D, Raza F, Najarian K, Hummel SL, Beard DA. medRxiv, DOI:10.1101/2024.11.11.24317106
    • Journal Article
      Learning using privileged information with logistic regression on acute respiratory distress syndrome detection.
      Gao Z, Cheng S, Wittrup E, Gryak J, Najarian K. Artif Intell Med, 2024 Oct; 156: 102947 DOI:10.1016/j.artmed.2024.102947
      PMID: 39208711
    • Journal Article
      Can Machine Learning Overcome the 95% Failure Rate and Reality that Only 30% of Approved Cancer Drugs Meaningfully Extend Patient Survival?
      Sun D, Macedonia C, Chen Z, Chandrasekaran S, Najarian K, Zhou S, Cernak T, Ellingrod VL, Jagadish HV, Marini B, Pai M, Violi A, Rech JC, Wang S, Li Y, Athey B, Omenn GS. J Med Chem, 2024 Sep 26; 67 (18): 16035 - 16055. DOI:10.1021/acs.jmedchem.4c01684
      PMID: 39253942
    • Journal Article
      A Comparison of Interpretable Machine Learning Approaches to Identify Outpatient Clinical Phenotypes Predictive of First Acute Myocardial Infarction.
      Hodgman M, Minoccheri C, Mathis M, Wittrup E, Najarian K. Diagnostics (Basel), 2024 Aug 10; 14 (16): DOI:10.3390/diagnostics14161741
      PMID: 39202229
    • Journal Article
      Prediction of pediatric peanut oral food challenge outcomes using machine learning.
      Gryak J, Georgievska A, Zhang J, Najarian K, Ravikumar R, Sanders G, Schuler CF. J Allergy Clin Immunol Glob, 2024 Aug; 3 (3): 100252 DOI:10.1016/j.jacig.2024.100252
      PMID: 38745865
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    Department News
    Meet DCMB's international visiting students, Summer 2024
    This summer and into the fall, DCMB is hosting three international students for up to six months each. They come from China, France and Korea, eager to learn and expand their education and experience through an extended visit at the University of Michigan (U-M) and DCMB.
    Department News
    DATA research call for proposals
    DATA research call for proposals in the DCMB at the U-M Medical School.
    Department News
    Kayvan Najarian received a Fulbright Specialist award
    Kayvan Najarian in the department of computational medicine and bioinformatics at the University of Michigan received a Fulbright Specialist award.
    Department News
    Clinical research and data science come together to improve diagnostic capabilities
    Clinical research and data science come together to improve diagnostic capabilities
    Department News
    AI in the Najarian Lab
    AI-based enhancement of medical diagnosis in disciplines such as emergency medicine and cardiology