Background: With advances in technology, teledermatology (TD) research has increased. However, an updated comprehensive quantitative analysis of TD research, especially one that identifies emerging trends of TD research in the coronavirus disease 2019 (COVID-19) era, is lacking. Objective: To conduct a scientometric analysis of TD research documents between 2002 and 2021 and explore the emerging trends. Methods: CiteSpace was used to perform scientometric analysis and yielded visualized network maps with corresponding metric values. Emerging trends were identified mainly through burst detection of keywords/terms, co-cited reference clustering analysis, and structural variability analysis (SVA). Results: A total of 932 documents, containing 27,958 cited references were identified from 2002 to 2021. Most TD research was published in journals from the "Dermatology" and "Health Care Sciences & Services" categories. American, Australian, and European researchers contributed the most research and formed close collaborations. Keywords/terms with strong burst values to date were "primary care," "historical perspective," "emerging technique," "improve access," "mobile teledermoscopy (TDS)," "access," "skin cancer," "telehealth," "recent finding," "artificial intelligence (AI)," "dermatological care," and "dermatological condition." Co-cited reference clustering analysis showed that the recently active cluster labels included "COVID-19 pandemic," "skin cancer," "deep neural network," and "underserved population." The SVA identified two reviews (Tognetti et al. and Mckoy et al.) that may be highly cited in the future. Conclusion: During and after the COVID-19 era, emerging trends in research on TD (especially mobile TDS) may be related to skin cancer and AI as well as further exploration of primary care in underserved areas.
Keywords: CiteSpace; bibliometrics; scientometric analysis; teledermatology; teledermoscopy; telemedcine; trends.