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Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models
Research article (Academic Radiology, 2023) · cited 13× · AI/ML
Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models
Summary
Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models is a scholarly article[1].
Key Facts
Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models'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). Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-learning-based-whole-lung-and-lung-lesion-quantification-despite-inconsistent-ground-truth-application-to-computeri
MLA“Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-learning-based-whole-lung-and-lung-lesion-quantification-despite-inconsistent-ground-truth-application-to-computeri.
BibTeX@misc{4ortxyz_deep-learning-based-whole-lung-and-lung-lesion-quantification-despite-inconsistent-ground-truth-application-to-computeri_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models}}, year = {2026}, url = {https://4ort.xyz/entity/deep-learning-based-whole-lung-and-lung-lesion-quantification-despite-inconsistent-ground-truth-application-to-computeri}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models — https://4ort.xyz/entity/deep-learning-based-whole-lung-and-lung-lesion-quantification-despite-inconsistent-ground-truth-application-to-computeri (retrieved 2026-05-24)
