Evidence map›Paper›PMID 33029064›Full record

ArticleFederal practitioner : for the health care professionals of the VA, DoD, and PHS2020

Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis.

Andrew A Borkowski, Narayan A Viswanadhan, L Brannon Thomas, Rodney D Guzman, Lauren A Deland, Stephen M Mastorides

Abstract read
In one paragraph

Article in Federal practitioner : for the health care professionals of the VA, DoD, and PHS, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Neuroimaging in the Era of Artificial Intelligence: Current Applications.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2022
    Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. CT Imaging Research Progress in COVID-19.Current medical imaging · 2022
    Review
  19. Review
  20. Artificial Intelligence and Precision Medicine: A Perspective.Advances in experimental medicine and biology · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Andrew A Borkowskiis Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida.
Narayan A Viswanadhanis Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida.
L Brannon Thomasis Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida.
Rodney D Guzmanis Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida.
Lauren A Delandis Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida.
Stephen M Mastoridesis Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronavirus disease-19 (COVID-19), caused by a novel member of the coronavirus family, is a respiratory disease that rapidly reached pandemic proportions with high morbidity and mortality. In only a few months, it has had a dramatic impact on society and world economies. COVID-19 has presented numerous challenges to all aspects of health care, including reliable methods for diagnosis, treatment, and prevention. Initial efforts to contain the spread of the virus were hampered by the time required to develop reliable diagnostic methods. Artificial intelligence (AI) is a rapidly growing field of computer science with many applications for health care. Machine learning is a subset of AI that uses deep learning with neural network algorithms. It can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans.

methodsIn this article, we explore the potential for the simple and widely available chest X-ray (CXR) to be used with AI to diagnose COVID-19 reliably. Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services. We utilized publicly available CXR images for patients with COVID-19 pneumonia, pneumonia from other etiologies, and normal CXRs as a dataset to train Microsoft CustomVision.

resultsOur trained model overall demonstrated 92.9% sensitivity (recall) and positive predictive value (precision), with results for each label showing sensitivity and positive predictive value at 94.8% and 98.9% for COVID-19 pneumonia, 89% and 91.8% for non-COVID-19 pneumonia, 95% and 88.8% for normal lung. We then validated the program using CXRs of patients from our institution with confirmed COVID-19 diagnoses along with non-COVID-19 pneumonia and normal CXRs. Our model performed with 100% sensitivity, 95% specificity, 97% accuracy, 91% positive predictive value, and 100% negative predictive value.

conclusionsWe have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward.

Identifiers

PMID33029064
PMCPMC7535959

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.