Crowd-sourcing optimized abdomen CT protocols from 908,000 examinations in a large radiation dose registry.

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Bibliographic Details
Title: Crowd-sourcing optimized abdomen CT protocols from 908,000 examinations in a large radiation dose registry.
Authors: Smith-Bindman R; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA. rebecca.smith-bindman@ucsf.edu.; Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA. rebecca.smith-bindman@ucsf.edu.; Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, CA, USA. rebecca.smith-bindman@ucsf.edu., Kang T; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA., Stewart C; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA., Chu PW; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA., Wang Y; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA., Szczykutowicz TP; Department of Radiology, University of Wisconsin, Madison, WI, USA.
Source: European radiology [Eur Radiol] 2026 May; Vol. 36 (5), pp. 3454-3464. Date of Electronic Publication: 2025 Nov 24.
Publication Type: Journal Article
Journal Info: Publisher: Springer International Country of Publication: Germany NLM ID: 9114774 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1084 (Electronic) Linking ISSN: 09387994 NLM ISO Abbreviation: Eur Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1432-1084
DOI:10.1007/s00330-025-12131-w