Idiopathic Pulmonary Fibrosis: The Association between the Adaptive Multiple Features Method and Fibrosis Outcomes.
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Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up.A Glimpse into the Future: Automated Quantitative Computed Tomography as a Biomarker in Idiopathic Pulmonary Fibrosis.Densitometric and local histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis.Reproducibility of airway luminal size in asthma measured by HRCT.Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications.Toward Early Identification of Clinically Relevant Interstitial Lung Disease.Investigating the effects of nintedanib on biomarkers of extracellular matrix turnover in patients with IPF: design of the randomised placebo-controlled INMARK®trial
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P2860
Idiopathic Pulmonary Fibrosis: The Association between the Adaptive Multiple Features Method and Fibrosis Outcomes.
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name
Idiopathic Pulmonary Fibrosis: ...... Method and Fibrosis Outcomes.
@en
Idiopathic Pulmonary Fibrosis: ...... Method and Fibrosis Outcomes.
@nl
type
label
Idiopathic Pulmonary Fibrosis: ...... Method and Fibrosis Outcomes.
@en
Idiopathic Pulmonary Fibrosis: ...... Method and Fibrosis Outcomes.
@nl
prefLabel
Idiopathic Pulmonary Fibrosis: ...... Method and Fibrosis Outcomes.
@en
Idiopathic Pulmonary Fibrosis: ...... Method and Fibrosis Outcomes.
@nl
P2093
P2860
P50
P1476
Idiopathic Pulmonary Fibrosis: ...... Method and Fibrosis Outcomes.
@en
P2093
David A Lynch
Edwin J R van Beek
Ella A Kazerooni
Fernando J Martinez
IPFnet Investigators
Junfeng Guo
Kevin R Flaherty
Susan Murray
P2860
P304
P356
10.1164/RCCM.201607-1385OC
P407
P577
2017-04-01T00:00:00Z