Citation

BibTex format

@inproceedings{Walsh:2025:10.1164/ajrccm.2025.211.Abstracts.A7680,
author = {Walsh, SL and Kanavati, F and Montiero, M and Sherlock, SP and Ble, F and Ostridge, K and Belvisi, MG and Molyneaux, P and Maher, TM and Johnson, SR and Saini, G and Thillai, M},
doi = {10.1164/ajrccm.2025.211.Abstracts.A7680},
publisher = {AMER THORACIC SOC},
title = {Deep Learning-Based Quantitative CT and CT Phenotype Classification Independently Predict Mortality in Idiopathic Pulmonary Fibrosis, a Prospective Observational Cohort Study},
url = {http://dx.doi.org/10.1164/ajrccm.2025.211.Abstracts.A7680},
year = {2025}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AU  - Walsh,SL
AU  - Kanavati,F
AU  - Montiero,M
AU  - Sherlock,SP
AU  - Ble,F
AU  - Ostridge,K
AU  - Belvisi,MG
AU  - Molyneaux,P
AU  - Maher,TM
AU  - Johnson,SR
AU  - Saini,G
AU  - Thillai,M
DO  - 10.1164/ajrccm.2025.211.Abstracts.A7680
PB  - AMER THORACIC SOC
PY  - 2025///
SN  - 1073-449X
TI  - Deep Learning-Based Quantitative CT and CT Phenotype Classification Independently Predict Mortality in Idiopathic Pulmonary Fibrosis, a Prospective Observational Cohort Study
UR  - http://dx.doi.org/10.1164/ajrccm.2025.211.Abstracts.A7680
ER  -
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