Classification of Visit-to-Visit Blood Pressure Variability: A Machine Learning Approach for Data Clustering on Systolic Blood Pressure Intervention Trial (SPRINT).
Kelvin Kam-fai TsoiMax W. Y. LamFelix C. H. ChanHoyee W. HiraiBaker K. K. BatSamuel Y. S. WongHelen Mei-Ling MengPublished in: DH (2017)
Keyphrases
- blood pressure
- data clustering
- heart rate
- unsupervised learning
- risk factors
- clustering algorithm
- k means
- cluster analysis
- spectral clustering
- decision trees
- pattern recognition
- blood glucose
- unsupervised feature selection
- text classification
- machine learning methods
- learning algorithm
- feature selection
- supervised learning
- feature extraction
- deterministic annealing