Histopathological Spectrum of Dermatological LesionsA Retrospective Study

Article Properties
Cite
Vedula, Bharadwaj, et al. “Histopathological Spectrum of Dermatological LesionsA Retrospective Study”. Journal of Evidence Based Medicine and Healthcare, vol. 7, no. 25, 2020, pp. 1198-02, https://doi.org/10.18410/jebmh/2020/256.
Vedula, B., Raksha, S., K, S. R., & R, S. R. N. (2020). Histopathological Spectrum of Dermatological LesionsA Retrospective Study. Journal of Evidence Based Medicine and Healthcare, 7(25), 1198-1202. https://doi.org/10.18410/jebmh/2020/256
Vedula B, Raksha S, K SR, R SRN. Histopathological Spectrum of Dermatological LesionsA Retrospective Study. Journal of Evidence Based Medicine and Healthcare. 2020;7(25):1198-202.
Citations
Title Journal Journal Categories Citations Publication Date
Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions IEEE Access
  • Technology: Electrical engineering. Electronics. Nuclear engineering
  • Science: Science (General): Cybernetics: Information theory
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
2023
A Histopathological Study of the Spectrum of Skin Lesions in a Tertiary Care Hospital: A Retrospective Study Cureus 2023
The Histomorphologic Profile of Skin Diseases in Kuwait Cureus 1 2023
Citations Analysis
The category Technology: Electrical engineering. Electronics. Nuclear engineering 1 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions and was published in 2023. The most recent citation comes from a 2023 study titled Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions. This article reached its peak citation in 2023, with 3 citations. It has been cited in 2 different journals, 50% of which are open access. Among related journals, the Cureus cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year