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Mohammad Samie Tootooni

Assistant Professor, Health Informatics and Data Science, Assoiate Director for CHOIR (Center for Health Outcomes and Informatics Research)

Health Sciences Campus

I am an assistant professor in the Department of Health Informatics and Data Science and Associate Director of the Center for Health Outcomes and Informatics Research at Loyola University Chicago. I received my PhD in Industrial and Systems Engineering (ISE) from Binghamton University in 2016. Prior to joining Loyola, I was a postdoctoral research associate in the Department of Health Sciences Research at Mayo Clinic in Rochester, Minnesota, for two years.

Research Interests

My research lies in the intersection of decision science and artificial intelligence, which furthers knowledge of monitoring of and predictive analytics for complex healthcare systems. I am particularly interested in the role of data science and artificial intelligence tools such as machine learning and natural language processing in development of clinical decision support models. Having an industrial and systems engineering background, I am also interested to apply systems thinking, quality assurance, and optimization principles to improve health outcomes. Furthermore, I teach two courses: Ontologies (knowledge representation) in Health and Natural Language Processing.

Education

  • PhD in Industrial and Systems Engineering, Binghamton University, Binghamton, New York
  • Postdoctoral Research Associate, Health Sciences Research, Mayo Clinic, Rochester, Minnesota

What prompted you to pursue your field?

What attracted  me to health informatics is first its uniquely interdisciplinary nature. This field brings together experts from medicine, computer science, engineering, public health and other field to solve real-world problem. I enjoy that both the coursework and the research are deeply collaborative, involving clinicians, researchers, and data scientists from different departments/schools/institutions. Working alongside diverse teams continually expands my perspective and strengthens systems thinking, which is is an essential skill for addressing complex clinical challenges. So, when you bring together this interdisciplinary team to deal with the challenges in healthcare, and you know that your work can directly improve people’s lives. I think this is inspiring. Our job is to try to develop innovative ideas and apply cutting-edge technologies to make care faster and more effective and affordable. I should say that maybe the most rewarding is that we get to train the next generation of scientists to carry this mission forward. Yes, I think this is inspiring.

What would you tell a student about why your field is exciting or important?

Artificial intelligence has an emerging role in decision making in different aspects of human life, and I believe it is fascinating that we can learn to utilize it in saving lives and improving patient care.

Publications

  • Large Language Model-Derived Digital Twins for Predicting Medication Treatments in the Intensive Care Unit, Afshar M., Tootooni M.S., Mayampurath A., Miller T., Churpek M.M., Gao Y., Dligach D., & Eslami B., American Journal of Respiratory and Critical Care Medicine, 211(Suppl.), A7181, 2025.

  • A Performance-Based Voting Framework for Assertion Detection in Clinical Notes, Eslami B., Dligach D., Strickland B., Azarvash N., & Tootooni M.S., Studies in Health Technology and Informatics, 329, 1125–1129, 2025.

  • The Association of Area Deprivation Index and Blood Pressure Control and Therapeutic Inertia Among Older Adults with Hypertension, Saban M.T., Tootooni S., Markossian T.W., Wozniak A., Hiura G.T., Probst B., Habicht K., & Kramer H.J., Journal of Human Hypertension, Advance online publication, 2025.

  • AI Models Powered by Emergency Medical Services Data Enhance Stroke Triage in Prehospital Settings, Saban M., Hiura G., de la Peña P., Wozniak A., Heiferman D., Akbilgic O., Cichon M., & Tootooni S., Unpublished manuscript, 2025.

  • AI-Based Preeclampsia Detection and Prediction with Electrocardiogram Data, Butler L., Gunturkun F., Chinthala L., Karabayir I., Tootooni M.S., Bakir-Batu B., Celik T., Akbilgic O., & Davis R.L., Frontiers in Cardiovascular Medicine, 11, 1360238, 2024.

  • Age and Comorbidities Are Associated with Therapeutic Inertia Among Older Adults with Uncontrolled Blood Pressure, Hiura G.T., Markossian T.W., Probst B.D., Tootooni M.S., Wozniak G., Rakotz M., & Kramer H.J., American Journal of Hypertension, 37(4), 280–289, 2024.

  • Determining Steady-State Trough Range in Vancomycin Drug Dosing Using Machine Learning, Tootooni M.S., Barreto E.F., Wutthisirisart P., Kashani K.B., & Pasupathy K.S., Journal of Critical Care, 82, 154784, 2024.

  • Feasibility of Remote Monitoring for Fatal Coronary Heart Disease Using Apple Watch ECGs, Butler L., Ivanov A., Celik T., Karabayir I., Chinthala L., Hudson M.M., Ness K.K., Mulrooney D.A., Dixon S.B., & Tootooni M.S., Cardiovascular Digital Health Journal, 5(3), 115–121, 2024.

  • DH-482888-003 ECG-AI Detection and Prediction of Preeclampsia, Butler L., Gunturkun F., Chinthala L., Karabayir I., Tootooni M.S., Bakir-Batu B., Celik T., Akbilgic O., & Davis L.R., Heart Rhythm, 21(5), S14, 2024.

  • Neighborhood Disadvantage Is Associated with Uncontrolled Blood Pressure and Therapeutic Inertia Among Older Adults with Hypertension, Saban M., Tootooni M.S., Markossian T., Wozniak A., Hiura G., Probst B., Habicht K., & Kramer H., Circulation, 150(Suppl. 1), A4141959, 2024.

  • ECG-AI to Assist with the Classification of Low Ejection Fraction and Heart Failure with Preserved Ejection Fraction, Karabayir I., Davis R., Tootooni M.S., Chinthala L., Soliman E., Jefferies J., Baykaner T., Shah S., Bertoni A., & Kitzman D., Circulation, 150(Suppl. 1), A4143513, 2024.

  • Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease: A Retrospective Study, Butler L., Ivanov A., Celik T., Karabayir I., Chinthala L., Tootooni M.S., Jaeger B.C., Patterson L.T., Doerr A.J., & McManus D.D., Journal of Cardiovascular Development and Disease, 11(12), 395, 2024.

  • Toward Digital Twins in the Intensive Care Unit: A Medication Management Case Study, Eslami B., Afshar M., Tootooni M.S., Miller T., Churpek M., Gao Y., & Dligach D., medRxiv, preprint doi:10.1101/2024.12.20.24319170, 2024.

  • Artificial Intelligence for Clinical Decision Support for Monitoring, Bibo R., Sabouniaghdam P., & Tootooni M.S., In Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine Vol. IV (p. 37), Frontiers Media SA, 2024.

  • Artificial Intelligence for Clinical Decision Support for Monitoring Patients in Cardiovascular ICUs: A Systematic Review, Moazemi S., Vahdati S., Li J., Kalkhoff S., Castano L.J.V., Dewitz B., Bibo R., Sabouniaghdam P., Tootooni M.S., & Bundschuh R.A., Frontiers in Medicine, 10, 1109411, 2023.

  • Discrepancy Between Perceptions and Acceptance of Clinical Decision Support Systems: Implementation of Artificial Intelligence for Vancomycin Dosing, Liu X., Barreto E.F., Dong Y., Liu C., Gao X., Tootooni M.S., Song X., & Kashani K.B., BMC Medical Informatics and Decision Making, 23(1), 157, 2023.

  • Feasibility of Remote Monitoring for Fatal Coronary Heart Disease from Single-Lead ECG, Butler L., Celik T., Karabayir I., Chinthala L., Tootooni M.S., McManus D.D., Herrington D., & Akbilgic O., Cardiovascular Digital Health Journal, 4(5), S1, 2023.

  • Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease, Butler L., Ivanov A., Celik T., Karabayir I., Chinthala L., Tootooni M.S., Jaeger B.C., Doerr A., McManus D.D., & Davis L.R., medRxiv, preprint doi:10.1101/2023.10.11.23296910, 2023.

  • Predicting risk of surgery in patients with small bowel Crohn’s disease strictures using computed tomography and magnetic resonance enterography, by Inoue, A., Bartlett, D. J., Shahraki, N., Sheedy, S. P., Heiken, J. P., Voss, B. A., Fidler, J. L., Tootooni, M. S., Sir, M. Y., & Pasupathy, K., published in Inflammatory Bowel Diseases, 28(11), 1677–1686, by Oxford University Press, 2022.

  • Image and structured data analysis for prognostication of health outcomes in patients presenting to the ED during the COVID-19 pandemic, by Butler, L., Karabayir, I., Tootooni, M. S., Afshar, M., Goldberg, A., & Akbilgic, O., published in International Journal of Medical Informatics, 158, Article 104662, by Elsevier, 2022.

  • Can prehospital data improve early identification of sepsis in emergency department? An integrative review of machine learning approaches, by Desai, M. D., Tootooni, M. S., & Bobay, K. L., published in Applied Clinical Informatics, 13(1), 189–202, by Georg Thieme Verlag, 2022.

  • Older age and higher number of comorbidities are associated with therapeutic inertia for blood pressure control, by Hiura, G. T., Markossian, T. W., Kramer, H. J., Probst, B. D., & Tootooni, M. S., published in Circulation, 146(Suppl 1), A12066–A12066, by American Heart Association, 2022.

  • Vancomycin dosing in intensive care unit patients: A machine learning approach, by Tootooni, M. S., Barreto, E. F., Wutthisirisart, P., Pasupathy, K., & Kashani, K., published in Critical Care Medicine, 49(1), 442, by Lippincott Williams & Wilkins, 2021.

  • The utilization of natural language processing in predicting emergency department overcrowding: A literature review, by de la Peña, P., & Tootooni, M. S., unpublished literature review, 2021.

  • Vancomycin dosing in critically ill patients: A machine learning approach, by Tootooni, M. S., Barreto, E. F., Pasupathy, K. S., & Kashani, K. B., presented in Proceedings of the AMIA Annual Symposium, 2021.

  • A sparse representation classification approach for near real-time, physics-based functional monitoring of aerosol jet-fabricated electronics, by Salary, R., Lombardi, J. P., Weerawarne, D. L., Tootooni, M. S., Rao, P. K., & Poliks, M. D., published in Journal of Manufacturing Science and Engineering, 142(8), 081007, by ASME, 2020.

  • Dialysis, COVID-19, poverty, and race in greater Chicago: An ecological analysis, by Bhayani, S., Sengupta, R., Markossian, T., Tootooni, S., Luke, A., Shoham, D., Cooper, R., & Kramer, H., published in Kidney Medicine, 2(5), 552–558.e1, by Elsevier, 2020.

  • Crohn’s disease small bowel strictures: Development and risk for surgery in patients with small bowel Crohn’s disease, by Inoue, A., Voss, B., Bartlett, D., Sheedy, S. P., Heiken, J., Shahraki, N., Sir, M., Pasupathy, K. S., Rieder, F., & Tootooni, M. S., published in Gastroenterology, 158(6), S-702, by Elsevier, 2020.

  • Distribution of SARS-CoV-2 positive tests, dialysis stations, and household poverty within Cook County, Illinois: PO0758, by Bhayani, S., Sengupta, R., Markossian, T., Tootooni, M. S., Luke, A., Shoham, D. A., Cooper, R., & Kramer, H. J., published in Journal of the American Society of Nephrology, 31(10S), 275–276, by Lippincott Williams & Wilkins, 2020.