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September 6, 2024Cancer Research and Treatment9 citationsOpen Access

Application of Machine Learning Algorithms for Risk Stratification and Efficacy Evaluation in Cervical Cancer Screening Among the ASCUS/LSIL Population: Evidence from the Korean HPV Cohort Study

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HSHeekyoung SongHLHong Yeon LeeSOShin Ah Oh

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Abstract

We assessed human papillomavirus (HPV) genotype-based risk stratification and the efficacy of cytology testing for cervical cancer screening in patients with atypical squamous cells of undetermined significance (ASCUS)/low-grade squamous intraepithelial lesion (LSIL).

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Song et al. (2024) studied this question.

synapsesocial.com/papers/68e59206b6db64358752d9behttps://doi.org/10.4143/crt.2024.465
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Clinical evaluation of an artificial intelligence-assisted cytological system among screening strategies for a cervical cancer high-risk population2024 · 13 citations
  2. 2Risk-Based Triage Using Cytology and HPV Genotyping to Reduce Unnecessary Colposcopy: A Real-World Cross-Sectional Study2026
  3. 3Findings to date from the ASCUS-LSIL Triage Study (ALTS).2003 · 206 citations
  4. 4Identifying Women With Cervical Neoplasia1999 · 585 citations
  5. 5Clinical Significance of Atypical Squamous Cells of Undetermined Significance (ASC-US) and Atypical Squamous Cells-Cannot Exclude High-Grade Squamous Intraepithelial Lesion (ASC-H) in a Low-Income Clinical Setting: A Retrospective Analysis2026