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Conference Paper Medical Time-series Prediction With LSTM-MDN-ATTN
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Authors
Hwin Dol Park, Youngwoong Han, Jae Hun Choi
Issue Date
2019-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.1359-1361
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC46691.2019.8939761
Abstract
We introduce the LSTM-MDN-ATTN model for predicting the medical time-series data. The LSTM-MDN-ATTN model predicts the future value of medical data by approximating the distribution of target data. Since medical data is multivariate data with various test items, attention mechanism is used to model the distribution suitable for target data. The attention layer used in this study predicts target data by focusing on the distribution that is related to the target data. The proposed LSTM-MDN-ATTN model shows better results compared to baseline models using lab test data from Asan Medical Center in Seoul.
KSP Keywords
Attention mechanism, Multivariate data, Target data, Test data, Time series data, lab test, medical data, time series prediction