A probabilistic ontology-based platform for self-learning context-aware healthcare applications.

•The architecture of a self-learning, ontology-based framework is presented.•Framework enables context-aware applications to change their behavior at run-time.•Knowledge added to the ontology is given a probability to convey its reliability.•An implemented use case is presented: mining the reasons for patients’ nurse calls.•Datasets of size >1000 with <5% noise yield correct results in negligible time.