Screened Web of Science Corpus on Explainable and Trustworthy AI in Medical Image Analysis: Bibliometric, Scoping and Topic-Modelling Data

Description

This dataset contains the processed bibliographic records used to support the study titled “Mapping the Shift from Performance to Trust in Medical Imaging AI: An Integrated Bibliometric, Scoping and Topic-Modelling Review.” The uploaded CSV file contains 801 records and 72 metadata fields extracted from the Web of Science Core Collection. The available fields include publication type, authors, affiliations, article titles, abstracts, author keywords, Keywords Plus, source titles, publication years, citation counts, cited references, DOI information, Web of Science categories, research areas, funding information and open-access status. The dataset was prepared for bibliometric mapping, scoping classification, publication and citation trend analysis, contributor and institutional analysis, and latent Dirichlet allocation topic modelling. It covers research relating to artificial intelligence in medical image analysis, including convolutional neural networks, transformer architectures, attention mechanisms, explainable artificial intelligence, medical-image classification, detection, segmentation, diagnosis, clinical decision support, interpretability, fairness and clinical translation. The dataset may support replication of the associated study, secondary bibliometric investigations, research-trend analysis, collaboration-network analysis and further text-mining studies. The current uploaded version contains records published between 2013 and 2026 and was exported from Web of Science on 8 February 2026.

Institutions

• Kaunas University of Technology

  Kaunas, Kaunas

Categories

Licence