Evaluating Multiplex Biomarkers for Early Detection of Cervical Cancer

Cervical cancer is still regarded as one of the most easily avoidable but prevalent cancers among women globally, especially in areas with little resources. Reducing the morbidity and mortality linked to this illness requires early detection. This review offers a thorough study of the most recent developments in cervical cancer screening methods, encompassing both established approaches like visual inspection with acetic acid (VIA), HPV DNA testing, and Pap smears as well as cutting-edge technologies like liquid-based cytology, biomarker detection, and AI-powered diagnostic tools. To increase sensitivity and specificity in early detection, special attention is paid to the integration of molecular diagnostics with AI-based systems. The study also identifies obstacles to the adoption of these technologies in low- and middle-income nations, where the burden is greatest, and suggests solutions. Lastly, we assess current clinical studies and potential avenues for improvement in screening techniques to guarantee prompt and precise identification of cervical precancerous lesions. The significance of easily accessible, effective, and reasonably priced screening programs for successful cervical cancer prevention and early intervention is emphasized by this review.

Authors

Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/icicnis64247.2024.10823117
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating Multiplex Biomarkers for Early Detection of Cervical Cancer

A. Grace Selvarani, M. Shanthini
1 citations
Radiomics and Machine Learning in Medical Imaging
0.40
article

Evaluating Multiplex Biomarkers for Early Detection of Cervical Cancer

A. Grace Selvarani, M. Shanthini
article en
1 citations

Abstract

Cervical cancer is still regarded as one of the most easily avoidable but prevalent cancers among women globally, especially in areas with little resources. Reducing the morbidity and mortality linked to this illness requires early detection. This review offers a thorough study of the most recent developments in cervical cancer screening methods, encompassing both established approaches like visual inspection with acetic acid (VIA), HPV DNA testing, and Pap smears as well as cutting-edge technologies like liquid-based cytology, biomarker detection, and AI-powered diagnostic tools. To increase sensitivity and specificity in early detection, special attention is paid to the integration of molecular diagnostics with AI-based systems. The study also identifies obstacles to the adoption of these technologies in low- and middle-income nations, where the burden is greatest, and suggests solutions. Lastly, we assess current clinical studies and potential avenues for improvement in screening techniques to guarantee prompt and precise identification of cervical precancerous lesions. The significance of easily accessible, effective, and reasonably priced screening programs for successful cervical cancer prevention and early intervention is emphasized by this review.

Good health and well-being
Openalex Percentile: Top 31%
Radiomics and Machine Learning in Medical Imaging
0.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.