Accurate stratification between VEXAS syndrome and differential diagnoses by deep learning analysis of peripheral blood smears.
VEXAS syndrome
autoinflammatory disorder
deep learning
myelodysplastic syndromes
Journal
Clinical chemistry and laboratory medicine
ISSN: 1437-4331
Titre abrégé: Clin Chem Lab Med
Pays: Germany
ID NLM: 9806306
Informations de publication
Date de publication:
27 06 2023
27 06 2023
Historique:
received:
18
12
2022
accepted:
17
01
2023
medline:
30
5
2023
pubmed:
2
2
2023
entrez:
1
2
2023
Statut:
epublish
Résumé
VEXAS syndrome is a newly described autoinflammatory disease associated with We compared leukocyte images from blood smears of three groups: participants with VEXAS syndrome (identified The VEXAS, UBA1-WT, and MDS groups included 3, 3, and 6 patients respectively. Analysis of 33,757 images of neutrophils and monocytes enabled us to distinguish VEXAS patients from both UBA1-WT and MDS patients, with mean ROC-AUCs ranging from 0.87 to 0.95. Image analysis of blood smears via deep learning accurately distinguished neutrophils and monocytes drawn from patients with VEXAS syndrome from those of patients with similar clinical and/or biological features but without
Identifiants
pubmed: 36722042
pii: cclm-2022-1283
doi: 10.1515/cclm-2022-1283
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1275-1279Informations de copyright
© 2023 Walter de Gruyter GmbH, Berlin/Boston.
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