Improving machine-learning development in allergology: bridging the gap between open-access and cohort-based databases

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.