Stacked Attention-based Networks for Accurate and Interpretable Health Risk Prediction-Reference-Cited by-同舟云学术

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Stacked Attention-based Networks for Accurate and Interpretable Health Risk Prediction

Published:2023-06-18 Issue: Volume: Page:
ISSN:
Container-title:2023 International Joint Conference on Neural Networks (IJCNN)
language:
Short-container-title:

Author:

Liu Yuxi¹,Zhang Zhenhao²,Thompson Campbell³,Leibbrandt Richard¹,Qin Shaowen¹,Yepes Antonio Jimeno⁴

Affiliation:

1. College of Science and Engineering, Flinders University,Adelaide,SA,Australia

2. College of Life Sciences, Northwest A&F University,Yangling,Shaanxi,China

3. School of Medicine, University of Adelaide,Adelaide,SA,Australia

4. School of Computing Technologies, RMIT University,Melbourne,Victoria,Australia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191099.pdf?arnumber=10191099

Reference34 articles.

1. INPREM: An Interpretable and Trustworthy Predictive Model for Healthcare

2. Self-attention enhanced patient journey understanding in healthcare system;peng;Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases,2020

3. Association of blood pressure and heart rate response during exercise with cardiovascular events in the Heart and Soul Study

4. Modeling long-term dependencies and short-term correlations in patient journey data with temporal attention networks for health prediction

5. An interpretable deep-learning model for early prediction of sepsis in the emergency department

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