Virtual Pooled Registry-Cancer Linkage System: an improved method for ascertaining cancer diagnoses

The VPR-CLS markedly improves ascertainment of cancer outcomes and is the preferred approach for determination of outcomes from cohort studies, postmarketing surveillance, and clinical trials.

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Publication Details

Journal
JNCI Monographs
Published
2024-08-01
DOI
https://doi.org/10.1093/jncimonographs/lgae005
Citations
3
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.21

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article

Virtual Pooled Registry-Cancer Linkage System: an improved method for ascertaining cancer diagnoses

Don Green, Annelie M Landgren, Betsy Kohler, Christopher J. Johnson et al.
3 citations
JNCI Monographs
Radiomics and Machine Learning in Medical Imaging
1.21
article

Virtual Pooled Registry-Cancer Linkage System: an improved method for ascertaining cancer diagnoses

Don Green, Annelie M Landgren, Betsy Kohler, Christopher J. Johnson, Dennis Deapen, Lynne Penberthy, Castine Clerkin, Anca Preda, William Howe, Joanne W. Elena
article en
3 citations

Abstract

The VPR-CLS markedly improves ascertainment of cancer outcomes and is the preferred approach for determination of outcomes from cohort studies, postmarketing surveillance, and clinical trials.

JNCI MonographsVol. 2024(65)
University of Southern California (US), North American Association of Central Cancer Registries (US), Information Management Services (US), National Cancer Institute (US)
Brigham and Women's Hospital, National Institutes of Health, National Cancer Institute
Openalex Percentile: Top 21%
Radiomics and Machine Learning in Medical Imaging
1.21
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Virtual Pooled Registry-Cancer Linkage System: an improved method for ascertaining cancer diagnoses — Don Green, Annelie M Landgren, et al. · JNCI Monographs (2024) | TGRS Research Map | TGRS