2025/09/09 by Daovisan, Hanvedes
#Medicine and Health Sciences #Science and Technology Studies #Social and Behavioral Sciences
paper · doi:10.17605/osf.io/enbz2
This review will undertake a scientometric mapping analysis of research on Explainable Artificial Intelligence (XAI) in healthcare published between 2018 and 2025. The purpose is to examine the intellectual structure, thematic trends, and emerging research pathways that characterise the integration of XAI into healthcare innovation. Particular emphasis will be placed on the re-emergence of rule-based systems as a mechanism for transparency, interpretability, and trustworthiness in AI-driven clinical decision support. The review will extract and analyse bibliometric data from international scientific databases to identify clusters, co-citation networks, keyword co-occurrence patterns, and thematic evolution. Visualisations such as co-word maps, strategic diagrams, and burst analyses will be employed to highlight research dynamics. Findings will provide insight into how rule-based approaches are shaping the explainability agenda in healthcare, identify research gaps, and generate policy-relevant recommendations for AI developers, healthcare professionals, and regulators to support the responsible and ethical deployment of explainable healthcare technologies.