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

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
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article

Data and code for Implementation Maturity, Reported Support, and Barriers in Hospital Artificial Intelligence Applications: Cross-Sectional Meta-Research Study

易跃雄, Warisijiang Kuerbanjiang, Guangle Dai, Musitapa Maimaitiaili et al.
1 links
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Data and code for Implementation Maturity, Reported Support, and Barriers in Hospital Artificial Intelligence Applications: Cross-Sectional Meta-Research Study

易跃雄, Warisijiang Kuerbanjiang, Guangle Dai, Musitapa Maimaitiaili, Xiaoyan He, Hui Xiao
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 19%
Artificial Intelligence in Healthcare and Education
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