Selected Publications
Mehta S, Tweedy E, Shi H, Ruiz VM, Morgan R, Sutton RM, Nishisaki A, Tsui RT: Machine learning-based prediction of critical deterioration in the pediatric intensive care unit. Critical Care Explorations March 2026 Notes: In Press.
Guan H, Tsui FR, Hsueh S, and Zhoua L: (Chapter 9) Bridging Theory and Practice: A Unified Framework for Evaluating AI in Healthcare and Biomedicine. Evaluating AI in Healthcare and Biomedicine: Foundations for Evidence-Based Decision Making in the Digital Age. Cresswell K, Prgomet M, and Weicken E (eds.). Springer Nature, March 2026 Notes: In presss.
Han S, Shi L, Kingsbury P, and Tsui FR: Enhanced Entity Matching between PubMed Authors and Research Institute’s Employees using Machine Learning. IEEE Access 13: 214803-214812, December 2025 Notes: DOI: 10.1109/access.2025.3642124.
Paul BT, Greeno C, Ryan ND, Tsui FR, Gibbons RD, Porta G, Joiner T, Brent D: A Prospective Examination of the Predictive Validity of Three Transdiagnostic Assessments of Risk for Suicidal Behavior: Psychache, the Interpersonal Theory of Suicide, and Reasons for Living. Journal of the American Academy of Child & Adolescent Psychiatry (JAACAP) November 2025 Notes: https://doi.org/10.1016/j.jaac.2025.11.010.
Silva L, Anderson D, Senthil K, Herrmann J, Starr J, Mason M, Morton S, Kilbaugh T, Morgan R, Tsui F, Ko T: Lactate-Pyruvate Ratio is Associated with Noninvasive Optical Measures of Cerebral Oxygenation in an Experimental Pediatric Model of Cardiac Arrest. Circulation 152(Suppl_3), November 2025.
Silva LEV, Chen CC, Press CA, Graham K, Shi L, Abend NS, Morgan RW, Topjian A, Tsui FR, Kirschen MP: Pediatric cardiac arrest outcome prediction using data-driven machine learning of early quantitative electroencephalogram (qEEG) features. Resuscitation Oct 2025 Notes: doi: 10.1016/j.resuscitation.2025.110854.
Visoki E, Moore TM, Ruiz VM, Fein JA, Calkins ME, Gur RC, Benton TD, Gur RE, Tsui FR, Barzilay R: Prediction of adolescent suicide attempt by integrating clinical, neurocognitive and geocoded neighborhood environment data. Schizophrenia Bulletin. Oxford University Press, 51(4): 895-905, July 2025 Notes: https://doi.org/10.1093/schbul/sbaf064.
Wachtendorf LJ, Xu X, Padiyath A, Simpao AF, Tsui FR, and Ma H: Artificial Intelligence and Machine Learning in Perioperative Monitoring. Cambridge Scholars Publishing. Liu H and Kaye AD (eds.). June 2025 Notes: ISBN: 978-1-0364-4063-3.
Kumar R, Skowno J, von Ungern‑Sternberg BS, Davidson A, Xu T, Zhang J,· Song X, Zhang M, Zhao P, Liu H, Jiang Y, Zuo Y, de Graaff JC, Vutskits L, Olbrecht VA, Szmuk P, Simpao AF, Tsui FR, Pratap JN, Padiyath A, Nelson O, Kurth CD, Yuan I, BRAIN Collaborative Investigators: Quantitative electroencephalogram and machine learning to predict expired sevoflurane concentration in infants. Journal of Clinical Monitoring and Computing May 2025 Notes: doi.org/10.1007/s10877-025-01301-2.
Tsui FR, Ruiz V, Shi L, Willet R, Goldsmith M: Predicting deterioration of single-ventricle patients in intensive care using bedside monitor data. Critical Care Medicine. LWW, 53(1), Jan. 2025.
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Last updated: 03/22/2026
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