Machine learning can identify an antinuclear antibody pattern that may rule out systemic autoimmune rheumatic diseases

13,671 ANA images from SLE patients enrolled in the Systemic Lupus International Collaborating Clinics Inception Cohort (SLICC, n = 2825 images), non-SLE subjects enrolled in the Ontario Health Study (OHS, n = 10,639 images), and the International Consensus on ANA Patterns (ICAP, n = 207 images) were analyzed. All SLICC and OHS ANA were performed in one central laboratory using IFA on HEp-2 cells (NovaLite, Werfen, SD) and read on a digital IFA microscope (NovaView, Werfen, SD). A lab

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