The Patient Journey to a First Diagnosis of Systemic Sclerosis: Temporal Disease Pattern Identification Using Machine Learning and Data Mining Among US and Japanese Patients

Del Galdo, F. orcid.org/0000-0002-8528-2283, Tian, Y., Di Donato, S. et al. (1 more author) (2023) The Patient Journey to a First Diagnosis of Systemic Sclerosis: Temporal Disease Pattern Identification Using Machine Learning and Data Mining Among US and Japanese Patients. In: ARTHRITIS & RHEUMATOLOGY. ACR Convergence 2023, 10-15 Nov 2023, San Diego, California. Vol 75. . Article no: 0117, pp. 206-208. ISSN: 2326-5191. EISSN: 2326-5205.

Metadata

Item Type: Conference abstract
Authors/Creators:
Keywords: autoimmune diseases, Diagnostic criteria, Disease Activity
Dates:
  • Published: 12 November 2023
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Institute of Rheumatology & Musculoskeletal Medicine (LIRMM) (Leeds) > Inflammatory Arthritis (Leeds)
Date Deposited: 23 Apr 2024 13:13
Last Modified: 05 Mar 2026 11:58
Published Version: https://acrabstracts.org/abstract/the-patient-jour...
Status: Published
Open Archives Initiative ID (OAI ID):

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