Internal validation of Automated Visual Evaluation (AVE) on smartphone images for cervical cancer screening in a prospective study in Zambia

Abstract Objectives Visual inspection with acetic acid (VIA) is a low‐cost approach for cervical cancer screening used in most low‐ and middle‐income countries (LMICs) but, similar to other visual tests, is subjective and requires sustained training and quality assurance. We developed, trained, and...

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Bibliografische gegevens

Hoofdauteurs:	Liming Hu, Mulindi H. Mwanahamuntu, Vikrant V. Sahasrabuddhe, Caroline Barrett, Matthew P. Horning, Ishan Shah, Zohreh Laverriere, Dipayan Banik, Ye Ji, Aaron Lunda Shibemba, Samson Chisele, Mukatimui Kalima Munalula, Friday Kaunga, Francis Musonda, Evans Malyangu, Karen Milch Hariharan, Groesbeck P. Parham
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	Wiley 2024-06-01
Reeks:	Cancer Medicine
Onderwerpen:	cancer prevention cancer risk factors deep learning epidemiology and prevention gynecological oncology machine learning
Online toegang:	https://doi.org/10.1002/cam4.7355
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