상세정보
학술대회
Medical Time-series Prediction With LSTM-MDN-ATTN
- 발행일
- 201910
- 출처
- International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.1359-1361
- 협약과제
- 19HS1500, 심혈관질환을 위한 인공지능 주치의 기술 개발, 김승환
- 초록
- 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 제안 키워드
- Attention mechanism, Lab test, Multivariate data, Target data, Test data, Time series data, medical data, time series prediction