Risk Assessment Model for Diabetic Cardiovascular Disease Via Personality and Time-Aware LSTM Network

Dehua Chen, Liping Zhang, Ming Zuo, Qiao Pan

2022

Abstract

Diabetic cardiovascular disease is one of the leading causes of disease death in the diabetic population and its prevention and treatment has become a major social challenge. It has attracted the attention of many scholars and experts around the world, and a lot of research work has been done on it. Most of them use cox proportional risk models to investigate the correlation between risk indicators and the risk of developing cardiovascular disease based on statistical methods, which lack attention to the heterogeneity of individual patient characteristics and disease contextual information. To fill this gap, we propose a new deep learning model, the Personality and Time-Aware LSTM (PT-LSTM), which is based on individual characteristics and time perception to assess the risk of developing cardiovascular disease in diabetes. The model is able to take into account the characteristics of chronic metabolic disease in diabetes, using information from long-term patient visits as input. The model uses the individual feature interaction layer to reweight the hidden information of disease information learned in the T-LSTM unit, resulting in a more accurate representation of disease information for the risk assessment task. We realistically evaluate our proposed model on this task and the experimental results show that our proposed model exhibits better performance. Compared to the baseline model, PT-LSTM achieves 93.49% AUROC on the dataset for this task, which is on average around 8.75% higher than the comparison model.

Paper Citation

in Harvard Style

Chen D., Zhang L., Zuo M. and Pan Q. (2022). Risk Assessment Model for Diabetic Cardiovascular Disease Via Personality and Time-Aware LSTM Network. In Proceedings of the 4th International Conference on Biotechnology and Biomedicine - Volume 1: ICBB; ISBN 978-989-758-637-8, SciTePress, pages 467-475. DOI: 10.5220/0012032600003633

in Bibtex Style

@conference{icbb22,
author={Dehua Chen and Liping Zhang and Ming Zuo and Qiao Pan},
title={Risk Assessment Model for Diabetic Cardiovascular Disease Via Personality and Time-Aware LSTM Network},
booktitle={Proceedings of the 4th International Conference on Biotechnology and Biomedicine - Volume 1: ICBB},
year={2022},
pages={467-475},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012032600003633},
isbn={978-989-758-637-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Biotechnology and Biomedicine - Volume 1: ICBB
TI - Risk Assessment Model for Diabetic Cardiovascular Disease Via Personality and Time-Aware LSTM Network
SN - 978-989-758-637-8
AU - Chen D.
AU - Zhang L.
AU - Zuo M.
AU - Pan Q.
PY - 2022
SP - 467
EP - 475
DO - 10.5220/0012032600003633
PB - SciTePress