A machine learning analysis to evaluate the outcome measures in inflammatory myopathies.

Journal: Autoimmunity reviews
PMID: 37142194

Abstract

OBJECTIVE: To assess the long-term outcome in patients with Idiopathic Inflammatory Myopathies (IIM), focusing on damage and activity disease indexes using artificial intelligence (AI).

Authors

  • Maria Giovanna Danieli
    SOS Immunologia delle Malattie Rare e dei Trapianti, AOU delle Marche & Dipartimento di Scienze Cliniche e Molecolari, Università Politecnica delle Marche, via Tronto 10/A, 60126 Torrette di Ancona, Italy; Postgraduate School of Allergy and Clinical Immunology, Università Politecnica delle Marche, via Tronto 10/A, 60126 Ancona, Italy. Electronic address: m.g.danieli@univpm.it.
  • Alberto Paladini
    Postgraduate School of Internal Medicine, Università Politecnica delle Marche, via Tronto 10/A, 60126 Ancona, Italy. Electronic address: albertopaladini1@gmail.com.
  • Eleonora Longhi
    Scuola di Medicina e Chirurgia, Alma Mater Studiorum, Università degli Studi di Bologna, 40126 Bologna, Italy. Electronic address: eleonora.longhi@studio.unibo.it.
  • Alessandro Tonacci
    Clinical Physiology Institute, National Research Council of Italy (IFC-CNR), Pisa Unit, 56124, Pisa, Italy.
  • Sebastiano Gangemi
    Clinical Physiology Institute, National Research Council of Italy (IFC-CNR), Messina Unit, 98125, Messina, Italy.

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