Code
01D25620
Duration
01 November 2020 → 31 October 2021
Funding
Regional and community funding: Special Research Fund
Promotor
Fellow
Research disciplines
-
Natural sciences
- Data mining
- Knowledge representation and reasoning
- Machine learning and decision making
- Health informatics
-
Medical and health sciences
- Mental healthcare services
Keywords
Interpretable machine learning
mental health-care
medical informatics
multimodal data fusion
confident machine learning
Project description
I will construct a multimodal and dynamic hierarchical sensing framework to tackle the challenges of personalized health monitoring in real-life settings. Multimodal sensing allows me to detect non-physiological symptoms by incorporating context. By fusing behavior modeling with hierarchical anomaly detection using an active learning approach, I will define the optimal moment to gather user feedback for the time dynamic models.