Search Results for author:
Found 6 papers, 0 papers with code
Clustered FedStack: Intermediate Global Models with Bayesian Information Criterion
In our study, we propose a novel Clustered FedStack framework based on the previously published Stacked Federated Learning (FedStack) framework.
QXAI: Explainable AI Framework for Quantitative Analysis in Patient Monitoring Systems
The deep learning models achieved state-of-the-art results in both prediction and classification tasks.
Natural Language Processing in Electronic Health Records in Relation to Healthcare Decision-making: A Systematic Review
Various Machine Learning (ML), Deep Learning (DL) and NLP techniques are studied and compared to understand the limitations and opportunities in this space comprehensively.
AI enabled RPM for Mental Health Facility
To provide a therapeutic environment for both patients and staff, aggressive or agitated patients need to be monitored remotely and track their vital signs and physical activities continuously.
Remote patient monitoring using artificial intelligence: Current state, applications, and challenges
The adoption of artificial intelligence (AI) in healthcare is growing rapidly.
FedStack: Personalized activity monitoring using stacked federated learning
The federated learning architecture was applied to these models to build local and global models capable of state of the art performances.
