The explainable AI (XAI) in healthcare: A bibliometric analysis using VOSviewer and R Studio

Özge Uysal Şahin; Sevda Akar

doi:10.26900/hsq.2847

Authors

Özge Uysal Şahin Canakkale Onsekiz Mart University / Türkiye 0000-0002-1422-4123
Sevda Akar Bandırma Onyedi Eylül University / Türkiye 0000-0003-1208-0258

10.26900/hsq.2847

Abstract

This study aims to perform a comprehensive bibliometric analysis to map the global research structure, evolution, and key trends of explainable XAI in healthcare. Utilizing Web of Science data (covering 2018–March 2025) and employing tools including VOSviewer and Bibliometrix, the analysis examined publication trends, keyword co-occurrence networks and centrality, thematic evolution, conceptual structure, author productivity, international collaboration networks, and co-citation patterns. Findings indicate exponential growth in XAI in healthcare research, peaking notably in 2024. “Explainable AI”, “machine learning”, and “deep learning” constitute the core conceptual basis, with “explainable AI” identified as structurally central. Key research themes driving the field, influential authors (e.g., Holzinger, Mueller, Guidotti, Lundberg, Ribeiro), major collaborating countries led by the USA and China, and foundational cited works were identified. Emerging themes like “fairness”, “transparency”, and “trust” were also emphasized. This bibliometric overview describes the dynamic landscape that defines XAI in healthcare, its main research areas, key players, and international collaboration networks, providing informative guidance for future research and development in this critical area.

Keywords:

Explainable AI (XAI) Web of Science science mapping bibliometric analysis VOSviewer Bibliometrix

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Author Biography

Özge Uysal Şahin, Canakkale Onsekiz Mart University / Türkiye

Doç. Dr.

ÇANAKKALE ONSEKİZ MART ÜNİVERSİTESİ/ÇANAKKALE UYGULAMALI BİLİMLER FAKÜLTESİ/SAĞLIK YÖNETİMİ BÖLÜMÜ/SAĞLIK EKONOMİSİ ANABİLİM DALI

The explainable AI (XAI) in healthcare: A bibliometric analysis using VOSviewer and R Studio

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Özge Uysal Şahin, Canakkale Onsekiz Mart University / Türkiye

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