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Found 13 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.
Adaptive Multi-Agent Deep Reinforcement Learning for Timely Healthcare Interventions
Effective patient monitoring is vital for timely interventions and improved healthcare outcomes.
PDRL: Multi-Agent based Reinforcement Learning for Predictive Monitoring
The PDRL framework is able to learn the future states of the traffic and weather forecasting and the cumulative rewards are gradually increasing over each episode.
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.
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
These issues compromise both the accuracy and the computational efficiency of models in both Machine Learning and Unlearning.
Graph-enabled Reinforcement Learning for Time Series Forecasting with Adaptive Intelligence
In this study, we propose a novel approach for predicting time-series data using GNN and monitoring with Reinforcement Learning (RL).
A Survey of Multimodal Information Fusion for Smart Healthcare: Mapping the Journey from Data to Wisdom
The components of the comprehensive survey presented in this paper form the foundation for more successful implementation of multimodal fusion in smart healthcare.
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy
Machine unlearning (MU) is gaining increasing attention due to the need to remove or modify predictions made by machine learning (ML) models.
Sentiment analysis and opinion mining on educational data: A survey
In the education sector, opinion mining is used to listen to student opinions and enhance their learning-teaching practices pedagogically.
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.
A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis
Research community approaches to extract the semantic meaning of emoticons and special characters in feedback which conveys user opinion and challenges in adopting NLP in education are explored.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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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.
