Global research of artificial intelligence in lung Cancer: A bibliometric and visualized study (Preprint)

Abstract

<sec> <title>BACKGROUND</title> In recent years, the rapid development of artificial intelligence (AI) has created new opportunities for lung cancer research, and a large number of academic research results have been published. </sec> <sec> <title>OBJECTIVE</title> We used a bibliometric approach to visualize and analyze the scientific research results related to AI in lung cancer in the 21st century, and summarize the current status and research hotspots in this field. </sec> <sec> <title>METHODS</title> Published scientific literature related to AI in lung cancer was searched in The Web of Science Core Collection (WoSCC). R software, Citespace, VOSviewer, Microsoft Excel 2019 and Tableau were used for bibliometric analysis and scientific mapping visualization. </sec> <sec> <title>RESULTS</title> The number of publications increased annually from 2000 to 2022, and the United States and Stanford University were the most influential countries and research institutions, respectively. The most prominent researcher is Philippe Lambin from Maastricht University Medical Centre in the Netherlands. Journal of Clinical Oncology is the most cited journal, and Frontiers in Oncology is the most productive journal. Machine learning (ML), deep learning (DL), pulmonary nodules, radiomics, and prognosis are the most frequently occurring keywords and trending topics in the field. </sec> <sec> <title>CONCLUSIONS</title> AI has a wide range of promising applications in lung cancer, and more and more researchers are devoted to this field of study. The results of our bibliometric analysis provide researchers with a more intuitive understanding of the current status and trends of research in this field. Quantitative and visual analysis can guide scholars worldwide in their research and exploration. </sec>

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