{
  "id": 9655,
  "url": "https://doi.org/10.1038/s41591-024-02850-w",
  "title": "Heterogeneity and predictors of the effects of AI assistance on radiologists",
  "summary": "The integration of artificial intelligence (AI) in medical image interpretation requires effective collaboration between clinicians and AI algorithms. Although previous studies demonstrated the potential of AI assistance in improving overall clinician performance, the individual impact on clinicians remains unclear. This large-scale study examined the heterogeneous effects of AI assistance on 140 radiologists across 15 chest X-ray diagnostic tasks and identified predictors of these effects. Surp",
  "authors": "Feiyang Yu, Alex Moehring, Oishi Banerjee, Tobias Salz, Nikhil Agarwal, Pranav Rajpurkar",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2024-03-01T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:57.583Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/9655",
  "original_url": "https://doi.org/10.1038/s41591-024-02850-w",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}