Advanced Cervical Cancer Diagnostic Systems: A Review of Innovations and Applications

Recent advances in cervical cancer diagnostics have transformed traditional screening approaches by integrating molecular, imaging, and digital innovations to enhance early detection, accuracy, and accessibility. High-risk HPV DNA testing has surpassed cytology in sensitivity, while emerging assays such as HPV mRNA detection, genotyping, and DNA methylation biomarkers (e.g., FAM19A4/miR124-2, CADM1/MAL) offer refined risk stratification and triage for HPV-positive women. Self-sampling and point-of-care molecular platforms improve screening reach, particularly in low-resource settings. Liquid biopsy techniques using circulating tumor DNA (ctDNA) and HPV-ctDNA hold promise for noninvasive disease monitoring and recurrence detection. Artificial intelligence (AI) and deep-learning systems enhance cytology and Colposcopic interpretation, addressing workforce shortages and improving diagnostic consistency. Additionally, radiomics, radiogenomics, and next-generation sequencing (NGS) contribute to personalized treatment planning and precision oncology. Despite these advances, barriers such as cost, infrastructure gaps, and limited large-scale validation persist. Standardization of molecular and AI tools and robust implementation research are needed to ensure global applicability. The integration of self-sampling, molecular triage, and AI-assisted diagnostics offers a scalable, equitable framework for cervical cancer control, particularly in resource-constrained environments.progress toward elimination. .