Generalizable deep neural networks for image quality classification of cervical images

Abstract Successful translation of artificial intelligence (AI) models into clinical practice, across clinical domains, is frequently hindered by the lack of image quality control. Diagnostic models are often trained on images with no denotation of image quality in the training data; this, in turn,...

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出版年:	Scientific Reports
主要な著者:	Syed Rakin Ahmed, Brian Befano, Didem Egemen, Ana Cecilia Rodriguez, Kanan T. Desai, Jose Jeronimo, Kayode O. Ajenifuja, Christopher Clark, Rebecca Perkins, Nicole G. Campos, Federica Inturrisi, Nicolas Wentzensen, Paul Han, Diego Guillen, Judy Norman, Andrew T. Goldstein, Margaret M. Madeleine, Yeycy Donastorg, Mark Schiffman, Silvia de Sanjose, Jayashree Kalpathy-Cramer, the PAVE Study Group
フォーマット:	論文
言語:	英語
出版事項:	Nature Portfolio 2025-02-01
主題:	Image quality Cervical cancer screening Artificial intelligence Deep learning
オンライン･アクセス:	https://doi.org/10.1038/s41598-025-90024-0