{
  "id": 8552,
  "url": "https://doi.org/10.1001/jamadermatol.2019.1735",
  "title": "Association Between Surgical Skin Markings in Dermoscopic Images and Diagnostic Performance of a Deep Learning Convolutional Neural Network for Melanoma Recognition",
  "summary": "IMPORTANCE: Deep learning convolutional neural networks (CNNs) have shown a performance at the level of dermatologists in the diagnosis of melanoma. Accordingly, further exploring the potential limitations of CNN technology before broadly applying it is of special interest. OBJECTIVE: To investigate the association between gentian violet surgical skin markings in dermoscopic images and the diagnostic performance of a CNN approved for use as a medical device in the European market. DESIGN AND SET",
  "authors": "Julia K. Winkler, Christine Fink, Ferdinand Toberer, Alexander Enk, Teresa Deinlein, Rainer Hofmann‐Wellenhof",
  "category": "research",
  "topics": "healthcare,finance-investment",
  "orgs": null,
  "regions": "eu",
  "published_at": "2019-08-15T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:39.872Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/8552",
  "original_url": "https://doi.org/10.1001/jamadermatol.2019.1735",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}