Bibliometric Assessment of Artificial Intelligence Applications in Acute Leukemia Research: A Systematic Analysis of Scientific Literature

Background and Aims: Citation analysis is a widely used method in research planning in which a publication receives citations by referencing other scholarly works. Through bibliometric analysis, the evolution of research domains and the influence of individual authors can be systematically assessed. This study aimed to identify and analyze the key characteristics of research on acute leukemia by examining the ۱۰۰ most-cited publications, with a specific focus on the application of artificial intelligence (AI) in leukemia research. Methods: On November ۲۱, ۲۰۲۴, a comprehensive search was conducted in the Web of Science database using the following keywords within the topic field: leukemia, blood malignancy, machine learning, transfer learning, artificial intelligence, deep learning, and IoT. Following an extensive retrieval process, all identified articles were ranked based on their citation counts, and the top ۱۰۰ most-cited articles were imported into EndNote ۲۱ for further analysis. Key bibliometric and methodological data were subsequently extracted using Excel and VOSviewer software, including: (۱) article title, (۲) authors, (۳) year of publication, (۴) journal name, (۵) impact factor, (۶) country of origin, (۷) number of citations, (۸) language, (۹) keywords, (۱۰) disease type, (۱۱) AI algorithms or techniques, (۱۲) study objective, (۱۳) study type, (۱۴) model performance evaluation methods, and (۱۵) data types used for training and testing AI models. Results: Among the ۱۰۰ most-cited articles in this field, ۵۷ focused specifically on acute leukemia. The average number of citations for these ۵۷ articles was ۵۰.۹۶, with the top three cited articles receiving ۳۶۲, ۳۰۹, and ۱۵۸ citations, respectively. All ۵۷ articles were published in English between ۲۰۱۱ and ۲۰۲۴. India emerged as the most prolific contributor, with ۱۳ publications. Conclusion: The bibliometric analysis revealed a notable increase in the application of artificial intelligence in acute leukemia research. The findings offer a clearer understanding of the AI methods employed and their effectiveness in this domain, enabling researchers to better identify key areas for future investigation and prioritize research efforts accordingly. Keywords: Artificial Intelligence, Leukemia, Deep Learning

کلیدواژه ها:

Artificial Intelligence ، Leukemia ، Deep Learning