A quantitative bibliometric evaluation of artificial intelligence in sustainable and digital healthcare based on scopus data (1995–2025)

Abstract

This study offers a comprehensive bibliometric and scientometric evaluation of research on artificial intelligence (AI), sustainability, and healthcare that was carried out between 1995 and 2025. The study addresses the growing need to understand how sustainable practices and digital transformation relate to one another in the healthcare industry. The PRISMA procedure was used to retrieve and carefully screen an initial dataset of 9,290 papers that were indexed by Scopus. A refined and verified collection of 419 relevant papers was kept for in-depth bibliometric analysis following the application of inclusion and exclusion criteria. VOSviewer (v1.6.20) and the R package Biblioshiny were used to perform keyword co-occurrence, co-authorship, and thematic-evolution analyses. The overall growth in publications was 708.33%, with an annual growth rate of 9.35%, according to quantitative statistics. Five major clusters were found through thematic mapping: AI-driven diagnostics, IoT-based patient monitoring, green hospital management, digital twins for healthcare infrastructure, and ethical frameworks for sustainable AI. The United States, the United Kingdom, and China together accounted for more than 48% of all publications worldwide, according to collaboration analysis. Analysis of time and burst shows that research increased exponentially after 2017, when AI-driven healthcare sustainability projects became more popular. Despite quick advancements, there are still significant gaps in the integrated frameworks that connect digital innovation with environmental policy. Overall, this study offers a data-driven mapping framework and a carefully selected, replicable dataset to help guide future investigations, the creation of policies, and calculated investments in globally sustainable, digitally enabled healthcare systems.

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