Evaluating the Potential Impact of AI on Urinary Tract Infection Diagnosis in the Emergency Department Across Demographic Groups: Retrospective Cohort Study

Mark Iscoe   ^{1, 2} , MD, MHS ;   Huan Li   ¹ , PhD ;   Haipeng Xue   ³ , MS ;   Vimig Socrates   ^{2, 4} , PhD ;   Aidan Gilson   ^{3, 5} , MD ;   Thomas Huang   ^{3, 6} , MD, MHS ;   Richard Andrew Taylor   ^{2, 7} , MD, MHS

¹ Department of Emergency Medicine, School of Medicine, Yale University, New Haven, CT, United States

² Department of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, United States

³ School of Medicine, Yale University, New Haven, CT, United States

⁴ Program of Computational Biology and Biomedical Informatics, Yale University, New Haven, CT, United States

⁵ Department of Opthalmology, Massachusetts Eye and Ear, Harvard University Medical School, Boston, MA, United States

⁶ Department of Emergency Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, United States

⁷ Department of Emergency Medicine, School of Medicine, University of Virginia, Charlottesville, VA, United States