Medical-Time-Series-Representation-Learning-via-Occlusion-Invariant-Feature

Pytorch implementation of "MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features",accepted in IEEE Journal of Biomedical and Health Informatics (JBHI).

JBHI version can be found here. Arxiv version can be found here.

@ARTICLE{10460072,
  author={Li, Huayu and Carreon-Rascon, Ana S. and Chen, Xiwen and Yuan, Geng and Li, Ao},
  journal={IEEE Journal of Biomedical and Health Informatics}, 
  title={MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features}, 
  year={2024},
  volume={},
  number={},
  pages={1-12},
  keywords={Time series analysis;Representation learning;Self-supervised learning;Brain modeling;Medical diagnostic imaging;Medical services;Computer vision;Medical time series;self-supervised learning;health monitoring;masked autoencoder;representation learning;time series classification;transformer},
  doi={10.1109/JBHI.2024.3373439}}