Keywords

Lung cancer screeningLung cancerMedicineFalse positive paradoxComputed tomographyCancerRadiologyMedical physicsArtificial intelligenceComputer scienceOncologyInternal medicine

MeSH Terms

AlgorithmsDatabasesFactualDeep LearningDiagnosisComputer-AssistedHumansImagingThree-DimensionalLung NeoplasmsMass ScreeningNeural NetworksComputerRetrospective StudiesRisk FactorsTomographyX-Ray ComputedUnited States

Affiliated Institutions

Related Publications

Overdiagnosis in Cancer

This article summarizes the phenomenon of cancer overdiagnosis-the diagnosis of a "cancer" that would otherwise not go on to cause symptoms or death. We describe the two prerequ...

2010 JNCI Journal of the National Cancer I... 1543 citations

ROC Methodology in Radiologic Imaging

If the performance of a diagnostic imaging system is to be evaluated objectively and meaningfully, one must compare radiologists' image-based diagnoses with actual states of dis...

1986 Investigative Radiology 1632 citations

Publication Info

Year
2019
Type
article
Volume
25
Issue
6
Pages
954-961
Citations
1862
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

1862
OpenAlex
70
Influential

Cite This

Diego Ardila, Atilla P. Kiraly, Sujeeth Bharadwaj et al. (2019). End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nature Medicine , 25 (6) , 954-961. https://doi.org/10.1038/s41591-019-0447-x

Identifiers

DOI
10.1038/s41591-019-0447-x
PMID
31110349

Data Quality

Data completeness: 72%