Artificial intelligence-based Raynaud's quantification index (ARTIX): an objective mobile-based tool for patient-centered assessment of Raynaud's phenomenon.

Journal: Arthritis research & therapy
Published Date: Jun 3, 2025

Abstract

BACKGROUND: We aimed to develop an artificial intelligence algorithm able to assess Raynaud's phenomenon (RP) from mobile phone photography, ensuring as a patient-centered, image-based method for RP quantification.

Authors

  • Marco Di Battista
    Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, LS7 4SA, UK.
  • Seda Colak
    Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, LS7 4SA, UK.
  • Anna Howard
    NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals Trust, Leeds, UK.
  • Francesca Donadoni
    Procedure Health Limited, London, UK.
  • Chris Owen-Smith
    Procedure Health Limited, London, UK.
  • Andrea Rindone
    Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, LS7 4SA, UK.
  • Stefano Di Donato
    Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, LS7 4SA, UK.
  • Collette Hartley
    Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, LS7 4SA, UK.
  • Lesley-Anne Bissell
    Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, LS7 4SA, UK.
  • Francesco Del Galdo
    Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, LS7 4SA, UK. f.delgaldo@leeds.ac.uk.

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