ArticleAnnals of medicine and surgery (2012)2026
Artificial intelligence in lung cancer: a bibliometric analysis of emerging trends and research hotspots.
Article in Annals of medicine and surgery (2012), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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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.
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Authors and funding
4 authors.
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Abstract
Background: Lung cancer remains the most common cause of global cancer-related deaths. With the rapid advancement of artificial intelligence (AI) in medicine, this study aims to review publications on AI applications in lung cancer and identify key research trends and hotspots. Methods: Publications from 1997 to 2022 on AI and lung cancer were retrieved from the Web of Science Core Collection. CiteSpace (5.7.R5) and VOSviewer (1.6.16) were used to analyze publication metrics, collaboration patterns, keyword clusters, and research trends. National cooperation was further assessed via the Bibliometric Online Analysis Platform. Results: Our results showed that the USA is the leading country in AI and lung cancer from all aspects. Followed by China, with the publication growing in recent years, and the cooperation between the USA and China is the most frequent. The USA expert Wenya Linda Bi has the most citations of 379, and Harvard Medical School has the most citations as institution of 959. However, Maastricht University has the most publications when it comes to the institution. During the past 25 years, the keywords of this field have changed a lot. In the past, the experts mainly focused on the "DNA." With the maturity of AI, the research hotspot evolved to "survival" and "diagnosis." Conclusion: AI and lung cancer research are integrating deeply, with areas like "AI + radiomics" advancing precise diagnosis and personalized treatment. This progress is expected to transform early screening and therapy while requiring continued improvements in technology and ethics.
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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 OpenQuestion graph.