Conference Paper, 2024

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

A13. TOWARDS IMPLEMENTATION: NEW BIOMARKERS IN ILD, Page a1007, 10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a1007

Contributors

Fainberg, Hernan P 0000-0001-9330-9047 [1] Moodley, Yuben P 0000-0002-4119-1734 [2] Triguero, Isaac 0000-0002-0150-0651 [3] Corte, Tamera Jo [4] Sand, Jannie Marie Bülow 0000-0002-3239-0934 [5] Leeming, Diana Julie [5] Karsdal, Morten Asser 0000-0002-4764-5100 [5] Renzoni, Elisabetta Augusta 0000-0002-1118-797X [6] Wells, Athol Umfrey [6] Fahy, William A 0000-0002-1018-0848 [7] Oballa, Eunice [7] Porte, Joanne [8] Saini, Gauri 0000-0002-7786-737X [8] Johnson, Simon Richard 0000-0002-9837-2763 [8] Wain, Louise V 0000-0003-4951-1867 [9] Molyneaux, Philip L 0000-0003-1301-8800 [1] Maher, Toby M 0000-0001-7192-9149 [1] Stewart, Iain D 0000-0002-1340-2688 [1] Jenkins, Richard Gisli 0000-0002-7929-2119 [1]

Affiliations

  1. [1] Imperial College London
    2. [NORA names: United Kingdom; Europe, Non-EU; OECD];
  2. [2] University of Western Australia
    3. [NORA names: Australia; Oceania; OECD];
  3. [3] University of Granada
    4. [NORA names: Spain; Europe, EU; OECD];
  4. [4] The University of Sydney
    5. [NORA names: Australia; Oceania; OECD];
  5. [5] Nordic Bioscience (Denmark)
    6. [NORA names: Nordic Bioscience; Private Research; Denmark; Europe, EU; Nordic; OECD];

Keywords

analysis, approach, biomarker signatures, blood, classification, classification of patients, cluster analysis, consensus, consensus clustering analysis, fibrosis, idiopathic pulmonary fibrosis, learning approach, machine learning approach, multiple machine learning approaches, patients, pulmonary fibrosis, signature

Data Provider: Digital Science

LINKS
-

Matching Records in NORA

  • No Matches Found

SUBJECTS
+

METRICS
+