{
  "id": 8608,
  "url": "https://doi.org/10.1186/s12859-019-2823-4",
  "title": "Deep convolutional neural networks for mammography: advances, challenges and applications",
  "summary": "BACKGROUND: The limitations of traditional computer-aided detection (CAD) systems for mammography, the extreme importance of early detection of breast cancer and the high impact of the false diagnosis of patients drive researchers to investigate deep learning (DL) methods for mammograms (MGs). Recent breakthroughs in DL, in particular, convolutional neural networks (CNNs) have achieved remarkable advances in the medical fields. Specifically, CNNs are used in mammography for lesion localization a",
  "authors": "Dina Abdelhafiz, Clifford Yang, Reda A. Ammar, Sheida Nabavi",
  "category": "research",
  "topics": "healthcare,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2019-06-01T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:39.876Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/8608",
  "original_url": "https://doi.org/10.1186/s12859-019-2823-4",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}