AI improves accuracy, agreement and efficiency of pathologists for Ki67 assessments in breast cancer

Autor: Amanda Dy, Ngoc-Nhu Jennifer Nguyen, Julien Meyer, Melanie Dawe, Wei Shi, Dimitri Androutsos, Anthony Fyles, Fei-Fei Liu, Susan Done, April Khademi
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Druh dokumentu: article
ISSN: 2045-2322
DOI: 10.1038/s41598-024-51723-2
Popis: Abstract The Ki-67 proliferation index (PI) guides treatment decisions in breast cancer but suffers from poor inter-rater reproducibility. Although AI tools have been designed for Ki-67 assessment, their impact on pathologists' work remains understudied. 90 international pathologists were recruited to assess the Ki-67 PI of ten breast cancer tissue microarrays with and without AI. Accuracy, agreement, and turnaround time with and without AI were compared. Pathologists’ perspectives on AI were collected. Using AI led to a significant decrease in PI error (2.1% with AI vs. 5.9% without AI, p
Databáze: Directory of Open Access Journals
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