Past, Present, And Future Of Global Research On Artificial Intelligence Applications In Dermatology: A Bibliometric Analysis

November 2023 in “ Medicine ”

Guangxin Wang, Xianguang Meng, Fan Zhang

artificial intelligence deep learning computer vision melanoma diagnosis teledermatology diagnostic accuracy data management randomized controlled trials prospective studies AI RCTs

Studysummary This study used bibliometric analysis to evaluate global research on AI applications in dermatology, identifying 406 relevant papers and highlighting current priorities such as machine learning for wound progression, AI in teledermatology, and applications for skin diseases. Our plain-language summary of this paper — not a Tressless recommendation.

The bibliometric analysis of AI applications in dermatology shows significant growth, with 406 papers published from 1970 to 2022. AI technologies like deep learning and computer vision have demonstrated diagnostic accuracy comparable to dermatologists, addressing challenges such as data management and dermatologist shortages. The United States leads in research output, with notable contributions from institutions like the University of California System and Memorial Sloan Kettering Cancer Center. Key research areas include AI-assisted melanoma diagnosis and teledermatology integration. The study calls for more randomized controlled trials and prospective studies, which currently represent a small fraction of the research, to further explore AI's role in enhancing dermatological diagnostics and treatments.

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Research cited in this study

3 / 3 results

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