| An unsupervised data-driven anomaly detection approach for adverse health conditions in people living with dementia: Cohort study N Bijlani, R Nilforooshan, S Kouchaki JMIR aging 5 (3), e38211, 2022 | 10 | 2022 |
| G-CMP: Graph-enhanced Contextual Matrix Profile for unsupervised anomaly detection in sensor-based remote health monitoring N Bijlani, OM Maldonado, S Kouchaki 33rd British Machine Vision Conference (BMVC) Proceedings, 2022 | 2 | 2022 |
| Graph Contrastive Learning for Anomaly Detection and Personalized Alerting in Sensor-based Remote Monitoring for Dementia Care N Bijlani, OM Maldonado, R Nilforooshan, P Barnaghi, S Kouchaki, ... Authorea Preprints, 2024 | 1 | 2024 |
| Explainable Anomaly Detection in Sensor-based Remote Healthcare Monitoring with Adaptive Temporal Contrast N Bijlani, G Carneiro, P Barnaghi, S Kouchaki ICLR 2024 Workshop on Learning from Time Series For Health, 2024 | | 2024 |
| A generalizable unsupervised graph‐based approach for anomalous event detection in people living with dementia N Bijlani, R Nilforooshan, OM Maldonado, S Kouchaki Alzheimer's & Dementia 19, e082103, 2023 | | 2023 |
| Interpreting Differentiable Latent States for Healthcare Time-series Data Y Chen, N Bijlani, S Kouchaki, P Barnaghi ICML 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH), 2023 | | 2023 |
| A lightweight unsupervised approach for adverse health detection and digital biomarker discovery in people living with dementia N Bijlani, R Nilforooshan, P Barnaghi, S Kouchaki Alzheimer's & dementia 19, e062198, 2023 | | 2023 |
