{
  "id": 8984,
  "url": "https://doi.org/10.1136/bmjopen-2020-047709",
  "title": "Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol",
  "summary": "INTRODUCTION: Standards for Reporting of Diagnostic Accuracy Study (STARD) was developed to improve the completeness and transparency of reporting in studies investigating diagnostic test accuracy. However, its current form, STARD 2015 does not address the issues and challenges raised by artificial intelligence (AI)-centred interventions. As such, we propose an AI-specific version of the STARD checklist (STARD-AI), which focuses on the reporting of AI diagnostic test accuracy studies. This paper",
  "authors": "Viknesh Sounderajah, Hutan Ashrafian, Robert Golub, Shravya Shetty, Jeffrey De Fauw, Lotty Hooft",
  "category": "research",
  "topics": "healthcare,transparency,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2021-06-01T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:47.098Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/8984",
  "original_url": "https://doi.org/10.1136/bmjopen-2020-047709",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}