Enhanced cervical precancerous lesions detection and classification using Archimedes Optimization Algorithm with transfer learning

Cervical cancer (CC) ranks as the fourth most common form of cancer affecting women, manifesting in the cervix. CC is caused by the Human papillomavirus (HPV) infection and is eradicated by vaccinating women from an early age. However, limited medical facilities present a significant challenge in mi...

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Veröffentlicht in:	Scientific reports Jg. 14; H. 1; S. 12076 - 14
Hauptverfasser:	Allogmani, Ayed S., Mohamed, Roushdy M., Al-shibly, Nasser M., Ragab, Mahmoud
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 27.05.2024 Nature Publishing Group Nature Portfolio
Schlagworte:	639/705/117 639/705/258 Algorithms Archimedes Optimization Algorithm Cervical cancer Classification Early Detection of Cancer - methods Female Human papillomavirus Humanities and Social Sciences Humans Lesions Long short-term memory Low income areas Machine Learning Medical image multidisciplinary Optimization algorithms Precancerous Conditions - diagnosis Science Science (multidisciplinary) Transfer learning Uterine Cervical Neoplasms - diagnosis Uterine Cervical Neoplasms - virology Medical image Human papillomavirus Archimedes Optimization Algorithm Transfer learning Cervical cancer
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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