ARTIFICIAL INTELLIGENCE FOR EARLY DETECTION OF CERVICAL CANCER: EVIDENCE-BASED DIAGNOSTIC SUPPORT AND A PROPOSED AI MODEL FOR UZBEKISTAN
Keywords:
Artificial intelligence; cervical cancer; cervical intraepithelial neoplasia; cervical cytology; Pap smear; ThinPrep; colposcopy; HPV; machine learning; diagnostic accuracy; clinical decision support; Uzbekistan.Abstract
Cervical cancer remains a major public health problem despite the availability of effective screening and preventive strategies. Artificial intelligence (AI) has increasingly been investigated as a tool for automated cytological interpretation, colposcopic image assessment, risk stratification, and clinical decision support. However, high diagnostic performance reported in individual studies cannot automatically be interpreted as evidence of clinical readiness because performance may vary according to population characteristics, disease prevalence, reference standards, imaging modalities, datasets, algorithms, and external validation procedures.
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