Classification of Patients With Idiopathic Pulmonary Fibrosis According to Blood Biomarker Signatures by Consensus Cluster Analysis: A Multiple Machine Learning Approach

被引：0
|
作者：
Fainberg, H. [1 ]
Moodley, Y. P. [2 ]
Triguero, I. [3 ]
Corte, T. [4 ]
Sand, J. M. [5 ]
Leeming, D. J. [6 ]
Karsdal, M. [7 ]
Renzoni, E.
Wells, A. U. [8 ]
Fahy, W. [9 ]
Oballa, E. [9 ]
Porte, J. [10 ,11 ]
Saini, G. [12 ,13 ]
Johnson, S. [13 ]
Wain, L. [14 ]
Molyneaux, P. L. [15 ]
Maher, T. [1 ]
Stewart, I. [1 ]
Jenkins, G. [1 ]
机构：
[1] Imperial Coll London, NHLI, London, England
[2] Univ Western Australia, Sch Med Pharmacol, Perth, Australia
[3] Univ Granada, Dept Comp Sci & Artificial Intelligence, Granada, Spain
[4] Univ Sydney, Sydney Med Sch, Sydney, NSW, Australia
[5] Nord Biosci, Pulm Res, Herlev, Denmark
[6] Nord Biosci, Fibrosis Hepat & Pulm Res, Herlev, Denmark
[7] Nord Biosci, Herlev, Denmark
[8] Royal Brompton Hosp, Resp, London, England
[9] GlaxoSmithKline, Discovery Med, Stevenage, England
[10] Univ Nottingham, Ctr Resp Res, Nottingham, England
[11] Univ Nottingham, NIHR Biomed Res Ctr, Nottingham, England
[12] Univ Nottingham, Nottingham, England
[13] Univ Nottingham, Resp Med, Nottingham, England
[14] Univ Leicester, Dept Populat Hlth Sci, Leicester, England
[15] Imperial Coll London, London, England
来源：
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE | 2024年 / 209卷
基金：
英国医学研究理事会;
关键词：
D O I：
暂无
中图分类号：
R4 [临床医学];
学科分类号：
1002 ; 100602 ;
摘要：
A1007
引用
收藏
页数：2
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