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Unsupervised Machine Learning Identifies Asthma Phenotypes in the Population-Based West Sweden Asthma Study

  • Muwada Bashir Awad Bashir
  • , Daniil Lisik
  • , Saliha Selin Ozuygur Ermis
  • , Rani Basna
  • , Reshed Abohalaka
  • , Selin Ercan
  • , Helena Backman
  • , Teet Pullerits
  • , Roxana Mincheva
  • , Göran Wennergren
  • , Madeleine Rådinger
  • , Jan Lötvall
  • , Linda Ekerljung
  • , Hannu Kankaanranta
  • , Bright I. Nwaru*
  • *Corresponding author for this work

Research output: Contribution to journalLetterScientific

2 Citations (Scopus)
8 Downloads (Pure)
Original languageEnglish
Pages (from-to)170-172
Number of pages3
JournalClinical and Experimental Allergy
Volume56
Issue number2
Early online date2025
DOIs
Publication statusPublished - Feb 2026
Publication typeB1 Journal article

Keywords

  • adults
  • asthma
  • cluster analysis
  • deep learning
  • phenotypes
  • population-based study
  • Sweden
  • unsupervised clustering

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology

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