ArticlePatterns (New York, N.Y.)2020
The Veterans Affairs Precision Oncology Data Repository, a Clinical, Genomic, and Imaging Research Database.
Article in Patterns (New York, N.Y.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Big Data and Artificial Intelligence in Cancer Drug Discovery: Promise, Challenges, and Emerging Opportunities.Cancers · 2026Review
- Managing, Analyzing and Sharing Research Data with Gen3 Data Commons.Scientific data · 2026Article
- The Pandemic Response Commons.JAMIA open · 2024Article
- Building Research Infrastructure to Develop Greater Learning Efficiencies (BRIDGE).Studies in health technology and informatics · 2024Article
- Transfer Learning for Mortality Prediction in Non-Small Cell Lung Cancer with Low-Resolution Histopathology Slide Snapshots.Studies in health technology and informatics · 2024Article
- Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons.Cold Spring Harbor molecular case studies · 2023Article
- A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.Nature medicine · 2023Article
- Bridging gaps between images and data: a systematic update on imaging biobanks.European radiology · 2022Review
- ProjectFlow: a configurable workflow management application for point of care research.JAMIA open · 2021Article
- Influential Usage of Big Data and Artificial Intelligence in Healthcare.Computational and mathematical methods in medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Veterans Affairs Precision Oncology Data Repository (VA-PODR) is a large, nationwide repository of de-identified data on patients diagnosed with cancer at the Department of Veterans Affairs (VA). Data include longitudinal clinical data from the VA's nationwide electronic health record system and the VA Central Cancer Registry, targeted tumor sequencing data, and medical imaging data including computed tomography (CT) scans and pathology slides. A subset of the repository is available at the Genomic Data Commons (GDC) and The Cancer Imaging Archive (TCIA), and the full repository is available through the Veterans Precision Oncology Data Commons (VPODC). By releasing this de-identified dataset, we aim to advance Veterans' health care through enabling translational research on the Veteran population by a wide variety of researchers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.