Artificial intelligence for abdominopelvic trauma imaging: trends, gaps, and future directions.
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| Title: | Artificial intelligence for abdominopelvic trauma imaging: trends, gaps, and future directions. |
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| Authors: | Dreizin D; University of Maryland Trauma Radiology AI Laboratory (TRAIL), University of Maryland School of Medicine, Baltimore, USA.; Department of Diagnostic Radiology and Nuclear Medicine, R Adams Cowley Shock Trauma Center, University of Maryland School of Medicine, Baltimore, USA., Cheng CT; Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital Linkou, Linkou, Taoyuan, Taiwan., Liao CH; Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital Linkou, Linkou, Taoyuan, Taiwan., Jindal A; University of Maryland Trauma Radiology AI Laboratory (TRAIL), University of Maryland School of Medicine, Baltimore, USA., Colak E; Department of Medical Imaging, University of Toronto, Toronto, Canada. Errol.Colak@UnityHealth.to.; Department of Medical Imaging, St. Michael's Hospital, Unity Health Toronto, Toronto, Canada. Errol.Colak@UnityHealth.to. |
| Source: | Abdominal radiology (New York) [Abdom Radiol (NY)] 2025 Oct; Vol. 50 (10), pp. 5028-5043. Date of Electronic Publication: 2025 Mar 21. |
| Publication Type: | Journal Article; Review; Research Support, N.I.H., Intramural |
| Journal Info: | Publisher: Springer Country of Publication: United States NLM ID: 101674571 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2366-0058 (Electronic) NLM ISO Abbreviation: Abdom Radiol (NY) Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2366-0058 |
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| DOI: | 10.1007/s00261-025-04816-z |
