ArticleJournal of clinical imaging science2025
Indian research on generative artificial intelligence in healthcare imaging: A comprehensive bibliometric analysis.
Article in Journal of clinical imaging science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study presents a comprehensive bibliometric analysis of Indian research on the application of generative artificial intelligence (GAI) in healthcare imaging from 2017 to 2025. It aims to evaluate the research output, citation impact, collaborative patterns, and key thematic areas to understand India's position in this rapidly evolving global landscape. Material and Methods: We used a comprehensive search strategy on the Scopus database, limited to publications with an Indian affiliation from 2017 to 2025. Data on author names, affiliations, publication years, keywords, and citations were extracted from 383 records. The analysis employed citation analysis, co-authorship networks, and keyword co-occurrence analysis, with VOSviewer software used for data visualization. Results: Globally, 2,761 papers were published in this field, with an average growth rate of 133.2%. India ranked third globally in publication volume with 383 papers, but its average citations per paper (CPP) were 6.55, much below the global average of 21.71. Conference papers dominated India's output (58.49%) but had a low CPP of 2.92, in contrast to higher-impact journal articles (11.29 CPP). Key institutions such as SRM Institute of Science and Technology were highly productive, while others, such as the GLA University, demonstrated high citation impact. The most prevalent keywords were "generative adversarial networks" and "medical imaging," highlighting a strong focus on technical applications. Conclusion: Indian research in GAI in healthcare imaging is marked by a significant increase in output, establishing the country as a major contributor. Although India ranks third globally in research output, its citation impact remains below the global average, reflecting the need to improve research quality, visibility, and international collaboration.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.