Early Indicators of the Impact of Using AI in Mammography Screening for Breast Cancer.
Journal
Radiology
ISSN: 1527-1315
Titre abrégé: Radiology
Pays: United States
ID NLM: 0401260
Informations de publication
Date de publication:
Jun 2024
Jun 2024
Historique:
medline:
4
6
2024
pubmed:
4
6
2024
entrez:
4
6
2024
Statut:
ppublish
Résumé
Background Retrospective studies have suggested that using artificial intelligence (AI) may decrease the workload of radiologists while preserving mammography screening performance. Purpose To compare workload and screening performance for two cohorts of women who underwent screening before and after AI system implementation. Materials and Methods This retrospective study included 50-69-year-old women who underwent biennial mammography screening in the Capital Region of Denmark. Before AI system implementation (October 1, 2020, to November 17, 2021), all screenings involved double reading. For screenings conducted after AI system implementation (November 18, 2021, to October 17, 2022), likely normal screenings (AI examination score ≤5 before May 3, 2022, or ≤7 on or after May 3, 2022) were single read by one of 19 senior full-time breast radiologists. The remaining screenings were read by two radiologists with AI-assisted decision support. Biopsy and surgical outcomes were retrieved between October 1, 2020, and April 15, 2023, ensuring at least 180 days of follow-up. Screening metrics were compared using the χ
Identifiants
pubmed: 38832880
doi: 10.1148/radiol.232479
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM