Discovery of temporal structure intricacy in arterial blood pressure waveforms representing acuity of liver transplant and forecasting short term surgical outcome via unsupervised manifold learning.
Shen-Chih WangChien-Kun TingCheng-Yen ChenChin-Su LiuNiang-Cheng LinChe-Chuan LoonHau-Tieng WuYu-Ting LinPublished in: CoRR (2021)
Keyphrases
- short term
- blood pressure
- manifold learning
- temporal structure
- semi supervised
- long term
- heart rate
- video data
- spatio temporal
- low dimensional
- forecasting model
- load forecasting
- dimensionality reduction
- temporal relations
- medium term
- risk factors
- unsupervised learning
- human activities
- dimension reduction
- high dimensional
- supervised learning
- short term and long term
- feature extraction
- arima model
- high dimensional data
- knowledge discovery
- labeled data
- data mining
- bag of features
- training data
- video sequences
- feature selection
- computer vision
- pairwise
- intraoperative