{
  "id": 8646,
  "url": "https://doi.org/10.1001/jamanetworkopen.2019.13436",
  "title": "Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions",
  "summary": "Importance: A high proportion of suspicious pigmented skin lesions referred for investigation are benign. Techniques to improve the accuracy of melanoma diagnoses throughout the patient pathway are needed to reduce the pressure on secondary care and pathology services. Objective: To determine the accuracy of an artificial intelligence algorithm in identifying melanoma in dermoscopic images of lesions taken with smartphone and digital single-lens reflex (DSLR) cameras. Design, Setting, and Partic",
  "authors": "Michael Phillips, Helen Marsden, W. Jaffe, Rubeta Matin, G.N. Wali, Jack Greenhalgh",
  "category": "research",
  "topics": "healthcare,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2019-10-16T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:39.878Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/8646",
  "original_url": "https://doi.org/10.1001/jamanetworkopen.2019.13436",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}