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Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study
Research article (The Lancet Digital Health, 2021) · cited 85× · AI/ML
Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study
Summary
Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study is a scholarly article[1].
Key Facts
Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study. Retrieved May 24, 2026, from https://4ort.xyz/entity/clinically-relevant-deep-learning-for-detection-and-quantification-of-geographic-atrophy-from-optical-coherence-tomograp
MLA“Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/clinically-relevant-deep-learning-for-detection-and-quantification-of-geographic-atrophy-from-optical-coherence-tomograp.
BibTeX@misc{4ortxyz_clinically-relevant-deep-learning-for-detection-and-quantification-of-geographic-atrophy-from-optical-coherence-tomograp_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study}}, year = {2026}, url = {https://4ort.xyz/entity/clinically-relevant-deep-learning-for-detection-and-quantification-of-geographic-atrophy-from-optical-coherence-tomograp}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study — https://4ort.xyz/entity/clinically-relevant-deep-learning-for-detection-and-quantification-of-geographic-atrophy-from-optical-coherence-tomograp (retrieved 2026-05-24)
