Evaluating AI-Enabled Healthcare Services: A bibliometric and topic modelling analysis of scholarly publications

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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Publication Details

Journal
Asia Pacific Journal of Health Management
Published
2025-09-16
DOI
https://doi.org/10.24083/apjhm.v20i2.4833
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluating AI-Enabled Healthcare Services: A bibliometric and topic modelling analysis of scholarly publications

Manisha Gupta, Sarita Mathur, Apoorva Verma, Anuj Kumar et al.
Asia Pacific Journal of Health Management
Artificial Intelligence in Healthcare and Education
article

Evaluating AI-Enabled Healthcare Services: A bibliometric and topic modelling analysis of scholarly publications

Manisha Gupta, Sarita Mathur, Apoorva Verma, Anuj Kumar, Yuganshu S.Tickoo
article en

Abstract

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.

Asia Pacific Journal of Health Management
Marwadi University (IN), Sharda University (IN)
Openalex Percentile: Top 82%
Artificial Intelligence in Healthcare and Education
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