Enhancing cervical cancer cytology screening via artificial intelligence innovation.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
22 08 2024
22 08 2024
Historique:
received:
07
02
2024
accepted:
20
08
2024
medline:
23
8
2024
pubmed:
23
8
2024
entrez:
22
8
2024
Statut:
epublish
Résumé
A double-check process helps prevent errors and ensures quality control. However, it may lead to decreased personal accountability, reduced effort, and declining quality checks. Introducing an artificial intelligence (AI)-based system in such scenarios could effectively address the risk of oversights. This study introduces an innovative AI-integrated workflow for cervical cytology screening that substantially improves efficiency and reduces the burden on cytologists. The AI model prioritizes cases for review based on anomaly scores and streamlines the first screening process to approximately 10 s per case. The model enhances the identification of high-risk cases via detailed microscopic observation, high anomaly scores cases, and a targeted review of low-score cases. The workflow highlights its capability for rapid, accurate, and less labor-intensive evaluations, demonstrating the potential to transform cervical cancer screening. This study highlights the importance of AI in modern medical diagnostics, particularly in areas with a high demand for accuracy and efficiency.
Identifiants
pubmed: 39174613
doi: 10.1038/s41598-024-70670-6
pii: 10.1038/s41598-024-70670-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
19535Subventions
Organisme : Grants-in-Aid for Scientific Research C
ID : 20K07370
Organisme : Grants-in-Aid for Scientific Research C
ID : 20K07370
Informations de copyright
© 2024. The Author(s).
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