The development of “automated visual evaluation” for cervical cancer screening: The promise and challenges in adapting deep‐learning for clinical testing

There is limited access to effective cervical cancer screening programs in many resource‐limited settings, resulting in continued high cervical cancer burden. Human papillomavirus (HPV) testing is increasingly recognized to be the preferable primary screening approach if affordable due to superior l...

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Veröffentlicht in:	International journal of cancer 2022-03, Vol.150 (5), p.741-752
Hauptverfasser:	Desai, Kanan T., Befano, Brian, Xue, Zhiyun, Kelly, Helen, Campos, Nicole G., Egemen, Didem, Gage, Julia C., Rodriguez, Ana‐Cecilia, Sahasrabuddhe, Vikrant, Levitz, David, Pearlman, Paul, Jeronimo, Jose, Antani, Sameer, Schiffman, Mark, de Sanjosé, Silvia
Format:	Artikel
Sprache:	eng
Schlagworte:	Acetic acid Adaptability Automation Cancer Cancer screening Cervical cancer Cervix Deep learning Human papillomavirus Medical research Medical screening Visual discrimination learning
Online-Zugang:	Volltext
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