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Code and Data Sharing Practices in the Radiology Artificial Intelligence Literature: A Meta-Research Study
31
Zitationen
4
Autoren
2022
Jahr
Abstract
Purpose: To evaluate code and data sharing practices in original artificial intelligence (AI) scientific manuscripts published in the Radiological Society of North America (RSNA) journals suite from 2017 through 2021. Materials and Methods: A retrospective meta-research study was conducted of articles published in the RSNA journals suite from January 1, 2017, through December 31, 2021. A total of 218 articles were included and evaluated for code sharing practices, reproducibility of shared code, and data sharing practices. Categorical comparisons were conducted using Fisher exact tests with respect to year and journal of publication, author affiliation(s), and type of algorithm used. Results: < .01). Conclusion: .© RSNA, 2022.
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