Enhancing accuracy and interpretability in EEG-based medical decision making using an explainable ensemble learning framework application for stroke prediction-Reference-Cited by-同舟云学术

Enhancing accuracy and interpretability in EEG-based medical decision making using an explainable ensemble learning framework application for stroke prediction

Published:2024-03 Issue: Volume:178 Page:114126
ISSN:0167-9236
Container-title:Decision Support Systems
language:en
Short-container-title:Decision Support Systems

Author:

Bouazizi Samar,Ltifi Hela

Publisher

Elsevier BV

Subject

Information Systems and Management,Arts and Humanities (miscellaneous),Developmental and Educational Psychology,Information Systems,Management Information Systems

Reference69 articles.

1. Stroke prediction using distributed machine learning based on apache spark;Ali;Stroke,2019

2. Acute single channel EEG predictors of cognitive function after stroke;Aminov;PLoS One,2017

3. Towards explainable deep neural networks (xDNN);Angelov;Neural Netw.,2020

4. Decision-making based on an improved visual analytics approach for emotion prediction;Bouazizi;Intell. Decis. Technol.,2023

5. Dynamic representation of time in brain states;Bueno;Sci. Rep.,2017

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on the Influence Mechanism of Digital Economy Based on Neural Networks on Corporate Governance Model;Journal of the Knowledge Economy;2024-08-27

2. How transparency affects algorithmic advice utilization: The mediating roles of trusting beliefs;Decision Support Systems;2024-08

3. Newman-Watts-Strogatz topology in deep echo state networks for speech emotion recognition;Engineering Applications of Artificial Intelligence;2024-07

4. Ethical and Privacy Considerations in AI-Driven AD Research;Advances in Medical Technologies and Clinical Practice;2024-06-28

5. FedDQA: A novel regularization-based deep learning method for data quality assessment in federated learning;Decision Support Systems;2024-05