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Improving machine-learning development in allergology: bridging the gap between open-access and cohort-based databases
0
Zitationen
4
Autoren
2026
Jahr
Abstract
Allergologists play a central role in building ML-ready resources. By ensuring rigorous clinical annotation, standardization of data, transparent methods, and independent validation, they can maximize the utility of OAD and CBD and their combination to accelerate progress toward precision allergy medicine.
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Autoren
Institutionen
- Max Delbrück Center(DE)
- German Centre for Cardiovascular Research(DE)
- Mercy Medical Center(US)
- Inserm(FR)
- Sorbonne Université(FR)
- Société Française d'Allergologie(FR)
- Centre d'Immunologie et des Maladies Infectieuses(FR)
- Université Paris Cité(FR)
- Sorbonne Paris Cité(FR)
- Assistance Publique – Hôpitaux de Paris(FR)
- Centre de Recherche Saint-Antoine(FR)
- Institut de Recherche pour le Développement(FR)
- Centre National de la Recherche Scientifique(FR)
- Université de Bordeaux(FR)
- ImmunoGen (United States)(US)
- Bordeaux Population Health(FR)
- Bipar(FR)
- Immungenetics (Germany)(DE)