Suchergebnisse - "Angelini, Elsa D."

PubPharm (68)

1

Robust deep labeling of radiological emphysema subtypes using squeeze and excitation convolutional neural networks: The MESA Lung and SPIROMICS Studies

enthalten in: arXiv.org | 2024

von Wysoczanski, A. | Ettehadi, N. | Arabshahi, S. | +10

2

Unsupervised Airway Tree Clustering with Deep Learning: The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study

enthalten in: arXiv.org | 2024

von Naik, S. | Angelini, E. | Barr, R. | +10

3

Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans

enthalten in: Thorax | 2023

von Angelini, E. | Yang, J. | Balte, P. | +38

CommentIn: Thorax. 2023 Nov;78(11):1063-1064. - PMID 37591700

4

Fibrosis severity scoring on Sirius red histology with multiple-instance deep learning

enthalten in: Biological imaging | 2023

von Naik, S. | Forlano, R. | Manousou, P. | +2

5

Quantification of lung ventilation defects on hyperpolarized MRI : The Multi-Ethnic Study of Atherosclerosis (MESA) COPD study

enthalten in: Magnetic resonance imaging | 2022

von Zhang, X. | Angelini, E. | Haghpanah, F. | +12

6

Post-natal growth of very preterm neonates - Authors' reply

enthalten in: The Lancet. Child & adolescent health | 2022

von Greenbury, S. | Angelini, E. | Ougham, K. | +4

CommentOn: Lancet Child Adolesc Health. 2021 Oct;5(10):719-728. - PMID 34450109

7

Novel Subtypes of Pulmonary Emphysema Based on Spatially-Informed Lung Texture Learning : The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study

enthalten in: IEEE transactions on medical imaging | 2021

von Yang, J. | Angelini, E. | Balte, P. | +5

8

Birthweight and patterns of postnatal weight gain in very and extremely preterm babies in England and Wales, 2008-19 : a cohort study

enthalten in: The Lancet. Child & adolescent health | 2021

von Greenbury, S. | Angelini, E. | Ougham, K. | +4

CommentIn: Lancet Child Adolesc Health. 2021 Oct;5(10):683-685. - PMID 34450108

9

Changes in neonatal admissions, care processes and outcomes in England and Wales during the COVID-19 pandemic : a whole population cohort study

enthalten in: BMJ open | 2021

von Greenbury, S. | Longford, N. | Ougham, K. | +4

10

Identification of variation in nutritional practice in neonatal units in England and association with clinical outcomes using agnostic machine learning

enthalten in: Scientific reports | 2021

von Greenbury, S. | Ougham, K. | Wu, J. | +4

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