Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Development of a cervical cancer progress prediction tool for human papillomavirus-positive Koreans: A support vector machine-based approach.

The Journal of international medical research - 1 Aug 2015

Kahng Jimin, Kim Eung-Hee, Kim Hong-Gee, Lee Wonbae

Abstract excerpt

OBJECTIVES: To develop a Web-based tool to draw attention to patients positive for human papillomavirus (HPV) who have a high risk of progression to cervical cancer, in order to increase compliance with follow-up examinations and facilitate good doctor-patient communication. METHODS: Records were retrospectively analysed from women who were positive for HPV on initial testing (before any treatment). Information...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Age Factors
Share to Biopsy

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Papillomaviridae

Share to Republic of Korea

Share to Sensitivity and Specificity

Share to Support Vector Machine

Share to Uterine Cervical Neoplasms

Share to Vaginal Smears

Source

Identifiers

PMID: 26001392
DOI: 10.1177/0300060515577846

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 8 closest

Development of a cervical cancer progress prediction tool for human papillomavirus-positive Koreans: A support vector machine-based approach.PMID 26001392Read ↗

Disease prediction model: An efficient machine learning- based DNA classifierSemantic proximity Read ↗

Cervical cancer screening uptake and its associated factor in Sub-Shara Africa: a machine learning approachSemantic proximity Read ↗

Classification of cervical cytology for human papilloma virus (HPV) infection using biospectroscopy and variable selection techniquesSemantic proximity Read ↗

Characteristics of high-risk human papillomavirus infection in women with abnormal cervical cytology: a population-based study in Shanxi Province, ChinaSemantic proximity Read ↗

Retrospective Analysis of the Association Between Cervical Squamous Intraepithelial Lesions and Human Papillomavirus GenotypesSemantic proximity Read ↗

Role of Human Papillomavirus in Various Cancers: Epidemiology, Screening and PreventionSemantic proximity Read ↗

Multi-center-validated machine learning model for cervical cancer based on human papillomavirus genotyping results.Semantic proximity Read ↗

Prevalence characteristics of human papillomavirus (HPV) infection among women receiving physical examinations in the Shangcheng District, Hangzhou city, China.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.