Artificial Intelligence in Cancer Screening: A Bibliometric Analysis of Advances in Early Detection Accuracy
DOI:
https://doi.org/10.24191/jikm.v15i1.3982Keywords:
Artificial Intelligence, Machine Learning, Cancer Screening, Cancer Diagnosis, Cancer Detection, Early Detection, AccuracyAbstract
Artificial intelligence (AI) has emerged as a transformative tool in cancer screening, offering significant improvements in early detection accuracy through advanced computational techniques such as machine learning and deep learning. This bibliometric analysis examines the global research landscape on AI in cancer screening, focusing on publication trends, influential contributors, thematic developments, and research gaps. Data was retrieved from Scopus, covering 8,793 records published between 2022 and 2024, with analysis spanning authorship, institutional contributions, source titles, and subject areas. The findings highlight a consistent growth in publications, peaking in 2024, with leading contributions from countries such as China, India, and the United States. Prominent institutions, including Princess Nourah Bint Abdulrahman University and the Ministry of Education of the People's Republic of China, have played pivotal roles in advancing the field. Keywords such as "machine learning," "deep learning," and "sensitivity and specificity" dominate the discourse, reflecting the focus on technological innovation and diagnostic accuracy. The subject areas of computer science, medicine, and engineering underscore the multidisciplinary nature of this research. Despite significant progress, critical gaps remain, particularly in addressing ethical challenges, ensuring dataset diversity, and expanding real-world implementation. This study emphasizes the importance of interdisciplinary collaboration and equitable integration of AI technologies into healthcare systems. The findings provide valuable insights for researchers, practitioners, and policymakers, highlighting future directions to maximize the impact of AI in revolutionizing cancer screening and improving patient outcomes globally.
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Copyright (c) 2025 Yudi Kurniawan Budi Susilo, Shamima Abdul Rahman, Faradiba Abdul Rasyid, Dewi Yuliana
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