Evidence map›Paper›PMID 36400764›Full record

ArticleNature communications2022

Developing medical imaging AI for emerging infectious diseases.

Shih-Cheng Huang, Akshay S Chaudhari, Curtis P Langlotz, Nigam Shah, Serena Yeung, Matthew P Lungren

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Sustaining High Reliability Amid Artificial Intelligence Adoption in Oncology.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Metaverse Wearables for Immersive Digital Healthcare: A Review.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Review
  12. Review
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.

Shih-Cheng HuangDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA. mschuang@stanford.edu.ORCID 0000-0001-9882-833X
Akshay S ChaudhariDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA.ORCID 0000-0002-3667-6796
Curtis P LanglotzDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA.ORCID 0000-0002-8972-8051
Nigam ShahDepartment of Biomedical Data Science, Stanford University, Stanford, CA, USA.ORCID 0000-0001-9385-7158
Serena Yeung *Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.ORCID 0000-0003-0529-0628
Matthew P Lungren *Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.

Funding

Population-level Pulmonary Embolism Outcome Prediction with Imaging and Clinical Data: A Multi-Center StudyR01HL155410 · NHLBI · STANFORD UNIVERSITY · PI LANGLOTZ, CURTIS P, SHAH, NIGAM H · 2021 to 2024
$2.1M
Deep Learning for Pulmonary Embolism Imaging Decision Support: A Multi-institutional CollaborationR01LM012966 · NLM · STANFORD UNIVERSITY · PI SHAH, NIGAM H · 2018 to 2021
$1.4M
NHLBI NIH HHS R01 HL155410NLM NIH HHS R01 LM012966U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI) R01HL155410U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine (NLM) R01LM012966
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Communicable Diseases, EmergingArtificial IntelligenceDiagnostic ImagingHumansRadiography

Identifiers

PMID36400764
PMCPMC9672573

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.