ReviewGigaScience2021
An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis.
Review in GigaScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 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
8 citing papers in PubMed.
- From Data Poverty to Data Sovereignty: Operationalizing Gold-Standard Biomedical Datasets in Low- and Middle-Income Countries.JMIR medical informatics · 2026Article
- MedImg: An Integrated Database for Public Medical Images.Genomics, proteomics & bioinformatics · 2025Article
- Successes and challenges in extracting information from DICOM image databases for audit and research.The British journal of radiology · 2023Review
- A pipeline to further enhance quality, integrity and reusability of the NCCID clinical data.Scientific data · 2023Article
- Delineating COVID-19 subgroups using routine clinical data identifies distinct in-hospital outcomes.Scientific reports · 2023Article
- Observational
- Bioinformatics, Computational Informatics, and Modeling Approaches to the Design of mRNA COVID-19 Vaccine Candidates.Computation (Basel, Switzerland) · 2022Article
- An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis.GigaScience · 2021Review
Corrections and comments
- Erratum issued
Authors and funding
16 authors.
Funding
Abstract
backgroundThe National COVID-19 Chest Imaging Database (NCCID) is a centralized database containing mainly chest X-rays and computed tomography scans from patients across the UK. The objective of the initiative is to support a better understanding of the coronavirus SARS-CoV-2 disease (COVID-19) and the development of machine learning technologies that will improve care for patients hospitalized with a severe COVID-19 infection. This article introduces the training dataset, including a snapshot analysis covering the completeness of clinical data, and availability of image data for the various use-cases (diagnosis, prognosis, longitudinal risk). An additional cohort analysis measures how well the NCCID represents the wider COVID-19-affected UK population in terms of geographic, demographic, and temporal coverage.
findingsThe NCCID offers high-quality DICOM images acquired across a variety of imaging machinery; multiple time points including historical images are available for a subset of patients. This volume and variety make the database well suited to development of diagnostic/prognostic models for COVID-associated respiratory conditions. Historical images and clinical data may aid long-term risk stratification, particularly as availability of comorbidity data increases through linkage to other resources. The cohort analysis revealed good alignment to general UK COVID-19 statistics for some categories, e.g., sex, whilst identifying areas for improvements to data collection methods, particularly geographic coverage.
conclusionThe NCCID is a growing resource that provides researchers with a large, high-quality database that can be leveraged both to support the response to the COVID-19 pandemic and as a test bed for building clinically viable medical imaging models.
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.