The Analysis of Proteomics by Machine Learning in Separating Idiopathic Pulmonary Fibrosis from Connective Tissue Disease–Interstitial Lung Disease

Yuben Moodley

doi:10.1164/rccm.202403-0603ED

The Analysis of Proteomics by Machine Learning in Separating Idiopathic Pulmonary Fibrosis from Connective Tissue Disease–Interstitial Lung Disease

Internal Medicine

Research output: Contribution to journal › Editorial › peer-review

Original language	English
Pages (from-to)	378-380
Number of pages	3
Journal	American Journal of Respiratory and Critical Care Medicine
Volume	210
Issue number	4
DOIs	https://doi.org/10.1164/rccm.202403-0603ED
Publication status	Published - 15 Aug 2024

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10.1164/rccm.202403-0603EDLicence: CC BY-NC-ND

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title = "The Analysis of Proteomics by Machine Learning in Separating Idiopathic Pulmonary Fibrosis from Connective Tissue Disease–Interstitial Lung Disease",

author = "Yuben Moodley",

year = "2024",

month = aug,

day = "15",

doi = "10.1164/rccm.202403-0603ED",

language = "English",

volume = "210",

pages = "378--380",

journal = "American Journal of Respiratory and Critical Care Medicine",

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publisher = "American Thoracic Society",

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T1 - The Analysis of Proteomics by Machine Learning in Separating Idiopathic Pulmonary Fibrosis from Connective Tissue Disease–Interstitial Lung Disease

AU - Moodley, Yuben

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SN - 1073-449X

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JF - American Journal of Respiratory and Critical Care Medicine

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ER -

The Analysis of Proteomics by Machine Learning in Separating Idiopathic Pulmonary Fibrosis from Connective Tissue Disease–Interstitial Lung Disease

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Circulatory biomarkers for IPF: improving patient outcomes

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The Analysis of Proteomics by Machine Learning in Separating Idiopathic Pulmonary Fibrosis from Connective Tissue Disease–Interstitial Lung Disease

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Circulatory biomarkers for IPF: improving patient outcomes

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