emerging technologies for early detection of cervical cancer: a narrative review of screening, molecular diagnostics, and artificial intelligence applications

Cervical cancer continues to represent a major global health burden, with disproportionately high incidence and mortality in low- and middle-income countries where access to organized screening and timely treatment remains limited. despite significant progress over past decades, early detection still relies on heterogeneous screening strategies with variable sensitivity, specificity, and accessibility across different healthcare systems.this narrative review critically examines recent advances in cervical cancer early detection, focusing on developments in screening modalities, molecular diagnostics, imaging innovations, and computational approaches. particular attention is given to liquid-based cytology, human papillomavirus (hpv)-based testing strategies, emerging biomarker panels, next-generation sequencing (ngs), and optical imaging technologies. in addition, the expanding role of artificial intelligence and machine learning in cytological interpretation, image analysis, and risk stratification is evaluated in terms of current evidence, clinical applicability, and translational limitations.rather than solely describing technological progress, this review emphasizes comparative effectiveness, implementation barriers, and real-world feasibility, particularly in resource-constrained settings. while several novel approaches demonstrate promising diagnostic performance in controlled or retrospective studies, their clinical utility remains limited by issues such as lack of large-scale prospective validation, cost constraints, infrastructural requirements, and variability in data quality.overall, integration of hpv vaccination programs with optimized, evidence-based screening strategies remains the most effective pathway toward reducing cervical cancer incidence and mortality. future progress will depend on strengthening health systems, improving accessibility of validated technologies, and ensuring equitable implementation of prevention strategies across diverse populations.