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Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation
Research article (Journal of Medical Systems, 2022) · cited 18× · AI/ML
Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation
Summary
Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation is a scholarly article[1].
Key Facts
Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation. Retrieved May 24, 2026, from https://4ort.xyz/entity/multicenter-study-on-covid-19-lung-computed-tomography-segmentation-with-varying-glass-ground-opacities-using-unseen-dee
MLA“Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/multicenter-study-on-covid-19-lung-computed-tomography-segmentation-with-varying-glass-ground-opacities-using-unseen-dee.
BibTeX@misc{4ortxyz_multicenter-study-on-covid-19-lung-computed-tomography-segmentation-with-varying-glass-ground-opacities-using-unseen-dee_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation}}, year = {2026}, url = {https://4ort.xyz/entity/multicenter-study-on-covid-19-lung-computed-tomography-segmentation-with-varying-glass-ground-opacities-using-unseen-dee}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Multicenter Study on COVID-19 Lung Computed Tomography Segmentation with varying Glass Ground Opacities using Unseen Deep Learning Artificial Intelligence Paradigms: COVLIAS 1.0 Validation — https://4ort.xyz/entity/multicenter-study-on-covid-19-lung-computed-tomography-segmentation-with-varying-glass-ground-opacities-using-unseen-dee (retrieved 2026-05-24)
