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Prediction model to identify patients with hypereosinophilic syndrome using real-world data

Background: Hypereosinophilic syndrome (HES) is challenging to diagnose and identify in real-world data. Objective: We sought to develop a machine learning model to predict HES diagnosis in secondary data and estimate HES prevalence among individuals with elevated blood eosinophil count (BEC). Metho...

Celý popis

Uloženo v:
Hlavní autoři: Paneez Khoury, MD, Yen Chung, PharmD, Donna Carstens, MD, Erin E. Cook, ScD, Fan Mu, ScD, Mu Cheng, MPH, Elizabeth Judson, MPH, Jingyi Chen, MSc, Travis Wang, MSc, Zhuo Chen, MPH, Princess U. Ogbogu, MD
Médium: Artigo
Jazyk:Inglês
Vydáno: Elsevier 2026-01-01
Edice:Journal of Allergy and Clinical Immunology: Global
Témata:
Hypereosinophilic syndrome
machine learning
prediction model
prevalence
On-line přístup:http://www.sciencedirect.com/science/article/pii/S2772829325001894
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