AI Development and Evaluation (AIDE)

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AI Development and Evaluation (AIDE) Lab
Department of Radiology
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AI Development and Evaluation (AIDE) Lab
Department of Radiology
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Recent Publications

  1. Armstrong B, Fang Z, Johnston A, Chang M, Koirala A, Na H, Gonzalez C, Larson DB. (2026). Sentence-Level Cross-Referencing Improves Comprehension and Confidence in AI-Generated Patient-Friendly Radiology Reports: Design for Understanding. Journal of the American College of Radiology, 23(6), 998–1007. https://doi.org/10.1016/j.jacr.2026.02.037
  2. Larson DB, Poff J, Krishnan S, Avondo J, Armstrong B, Na H, Chaudhari A, Kottler, N. (2026). Predicting the Value of Radiology Artificial Intelligence Applications: Large-Scale Predeployment Evaluation of a Portfolio of Models. American Journal of Roentgenology. https://doi.org/10.2214/AJR.25.34340
  3. Fang Z, Johnston A, Cheuy LY, Na H, Paschali M, Gonzalez C, Armstrong B, Koirala A, Laurel D, Campion A, Iv M, Chaudhari A, & Larson DB. (2025). Automated real-time assessment of intracranial hemorrhage detection AI using an ensembled monitoring model (EMM). Npj Digital Medicine, 8(1). https://doi.org/10.1038/s41746-025-02007-0
  4. Larson DB, Koirala A, Cheuy LY, Paschali M, Van Veen, D, Na H, Petterson, MB, Fang Z, Chaudhari A. Assessing Completeness of Clinical Histories Accompanying Imaging Orders Using Adapted Open-Source and Closed-Source Large Language Models. Radiology. 2025 February;314(2). https://doi.org/10.1148/radiol.241051
  5. Paschali M, Chen Z, Blankemeier L, Varma M, Youssef A, Bluethgen C, Langlotz C, Gatidis S, Chaudhari A. Foundation Models in Radiology: What, How, Why, and Why Not. Radiology, 2025 February;314(2). https://doi.org/10.1148/radiol.240597