Endotyping allergic rhinitis in children: A machine learning approach-Reference-Cited by-同舟云学术

Endotyping allergic rhinitis in children: A machine learning approach

Published:2022-01 Issue:S27 Volume:33 Page:18-21
ISSN:0905-6157
Container-title:Pediatric Allergy and Immunology
language:en
Short-container-title:Pediatric Allergy Immunology

Author:

Malizia Velia¹^ORCID,Cilluffo Giovanna¹^ORCID,Fasola Salvatore¹^ORCID,Ferrante Giuliana²^ORCID,Landi Massimo¹³^ORCID,Montalbano Laura¹^ORCID,Licari Amelia⁴⁵^ORCID,La Grutta Stefania¹^ORCID

Affiliation:

1. Institute for Biomedical Research and Innovation National Research Council Palermo Italy

2. Department of Health Promotion, Mother and Child Care Internal Medicine and Medical Specialties University of Palermo Palermo Italy

3. Pediatric National Healthcare System Turin Italy

4. Pediatric Clinic Fondazione IRCCS Policlinico San Matteo Pavia Italy

5. Department of Clinical, Chirurgical, Diagnostic and Pediatric Science University of Pavia Pavia Italy

Publisher

Wiley

Subject

Immunology,Immunology and Allergy,Pediatrics, Perinatology and Child Health

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/pai.13620

Reference10 articles.

1. The Burden of Rhinitis and Rhinoconjunctivitis in Adolescents

2. An essential role for dendritic cells in human and experimental allergic rhinitis

3. Nasal cytology: Methodology with application to clinical practice and research

4. New concepts in pediatric rhinitis

5. A survey around the Italian pediatric units on current clinical practice for Sleep Disordered Breathing (SDB)

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