Predicting Invasive Coronary Perfusion Pressure Using Noninvasive Electrocardiogram and Photoplethysmography Based on Machine Learning for Cardiopulmonary Resuscitation.
Shuxin ChenLijun JiangKe LiChang PanJiaojiao PangFeng XuJiali WangYuguo ChenPublished in: CISP-BMEI (2022)
Keyphrases
- machine learning
- blood flow
- myocardial perfusion
- coronary artery disease
- machine learning methods
- pattern recognition
- data analysis
- artificial intelligence
- decision trees
- machine learning algorithms
- knowledge acquisition
- data mining
- learning algorithm
- x ray
- natural language processing
- text classification
- left ventricle
- computer science
- supervised learning
- heart rate
- automated analysis
- information extraction
- spect images
- computer vision