Data and code for Implementation Maturity, Reported Support, and Barriers in Hospital Artificial Intelligence Applications: Cross-Sectional Meta-Research Study
Article-level data and reproducible analysis code supporting a cross-sectional meta-research study of implementation maturity, reported support, governance, and barriers in hospital artificial intelligence applications. The package contains 698 included article reports, 16,752 coded item rows across 24 items, a 1,012-record included/excluded comparison dataset, source evidence locators, complete item and scoring codebooks, aggregate paired-rating matrices, portable R and Python scripts, numerical reference tables, and regenerated outputs. Analyses include descriptive estimates, Firth logistic models, exact barrier comparisons, bootstrap differences, reporting-context sensitivities, a joint-score model, selection comparisons, and agreement statistics. A full rerun verified 43 reference CSV tables, agreement estimates and governance-score composition. Observations concern publication-level reporting and do not establish causal effects or institution-level governance performance.
Authors
- 易跃雄
- Warisijiang Kuerbanjiang (ORCID: https://orcid.org/0009-0008-2540-0613)
- Guangle Dai (ORCID: https://orcid.org/0009-0008-6457-1968)
- Musitapa Maimaitiaili (ORCID: https://orcid.org/0009-0008-6457-1968)
- Xiaoyan He
- Hui Xiao
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-31
- DOI
- https://doi.org/10.5281/zenodo.23816002
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00