Bibliometric analysis reveals key themes in artificial intelligence healthcare studies, suggesting a focus on diagnosis and service quality.
This study examines emerging topics and trends in Artificial Intelligence (AI)-enabled healthcare services, with a particular emphasis on service quality, diagnosis, and treatment enhancement due to the emergence of technology. This study aimed to identify the primary themes found in scholarly publications and examine how those themes have significance in the healthcare sector. Bibliometric and topic modelling techniques were used to analyse the extracted set of relevant publications. For bibliometric analysis, the bibliometric package Biblioshiny was used in R version 4.4.1, and Latent Dirichlet Allocation (LDA) was utilised for topic modelling. Academic papers from Scopus are included in the dataset, covering the period from 2011 to 2024. The research analysis highlights that there is a substantial emphasis placed on the use of artificial intelligence in the healthcare industry, notably in the areas of improving diagnosis, treatment personalisation, and operational efficiency related to services provided in the healthcare sector.
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Verma et al. (2025) studied this question.
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