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

作者信息

Moodley Yuben

机构信息

Faculty of Medicine University of Western Australia Perth, Western Australia, Australia.

Department of Respiratory Medicine Fiona Stanley Hospital Murdoch, Western Australia, Australia.

出版信息

Am J Respir Crit Care Med. 2024 Aug 15;210(4):378-380. doi: 10.1164/rccm.202403-0603ED.

DOI:10.1164/rccm.202403-0603ED
PMID:38593003
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11351808/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2f6/11351808/465c41750410/rccm.202403-0603EDf1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2f6/11351808/465c41750410/rccm.202403-0603EDf1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2f6/11351808/465c41750410/rccm.202403-0603EDf1.jpg

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本文引用的文献

1
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Am J Respir Crit Care Med. 2024 Aug 15;210(4):444-454. doi: 10.1164/rccm.202309-1692OC.
2
Prevalence, imaging patterns and risk factors of interstitial lung disease in connective tissue disease: a systematic review and meta-analysis.结缔组织病相关性间质性肺疾病的流行情况、影像学表现及危险因素：系统评价和荟萃分析。
Eur Respir Rev. 2023 Mar 8;32(167). doi: 10.1183/16000617.0210-2022. Print 2023 Mar 31.
3
Unsupervised machine learning identifies predictive progression markers of IPF.
无监督机器学习可识别特发性肺纤维化的预测进展标志物。
Eur Radiol. 2023 Feb;33(2):925-935. doi: 10.1007/s00330-022-09101-x. Epub 2022 Sep 6.
4
Robust biomarker screening from gene expression data by stable machine learning-recursive feature elimination methods.基于稳健机器学习-递归特征消除方法的基因表达数据的稳健生物标志物筛选。
Comput Biol Chem. 2022 Oct;100:107747. doi: 10.1016/j.compbiolchem.2022.107747. Epub 2022 Jul 29.
5
Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography.基于深度学习的高分辨率计算机断层扫描对进展性肺纤维化疾病的预后预测。
Am J Respir Crit Care Med. 2022 Oct 1;206(7):883-891. doi: 10.1164/rccm.202112-2684OC.
6
Biomarker signatures for progressive idiopathic pulmonary fibrosis.进行性特发性肺纤维化的生物标志物特征。
Eur Respir J. 2022 Mar 31;59(3). doi: 10.1183/13993003.01181-2021. Print 2022 Mar.
7
Estimation of the Prevalence of Progressive Fibrosing Interstitial Lung Diseases: Systematic Literature Review and Data from a Physician Survey.评估进行性纤维化性间质性肺病的患病率：系统文献复习和医生调查数据。
Adv Ther. 2021 Feb;38(2):854-867. doi: 10.1007/s12325-020-01578-6. Epub 2020 Dec 14.
8
The Pulmonary Fibrosis Foundation Patient Registry. Rationale, Design, and Methods.肺纤维化基金会患者登记处。原理、设计和方法。
Ann Am Thorac Soc. 2020 Dec;17(12):1620-1628. doi: 10.1513/AnnalsATS.202001-035SD.
9
Artificial Intelligence and Machine Learning in Pathology: The Present Landscape of Supervised Methods.病理学中的人工智能与机器学习：监督方法的现状
Acad Pathol. 2019 Sep 3;6:2374289519873088. doi: 10.1177/2374289519873088. eCollection 2019 Jan-Dec.
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Analysis by proteomics reveals unique circulatory proteins in idiopathic pulmonary fibrosis.蛋白质组学分析揭示特发性肺纤维化中的独特循环蛋白。
Respirology. 2019 Nov;24(11):1111-1114. doi: 10.1111/resp.13668. Epub 2019 Aug 8.