Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning.
Alena OrlenkoDaniel KofinkLeo-Pekka LyytikäinenKjell NikusPashupati P. MishraPekka KuukasjärviPekka J. KarhunenMika KähönenJari O. LaurikkaTerho LehtimäkiFolkert W. AsselbergsJason H. MoorePublished in: Bioinform. (2020)
Keyphrases
- model selection
- coronary artery disease
- machine learning
- cardiovascular disease
- diagnostic process
- cross validation
- myocardial perfusion
- spect images
- clinical setting
- medical diagnosis
- hyperparameters
- clinical diagnosis
- parameter estimation
- sample size
- clinical practice
- decision support system
- model based diagnosis
- selection criterion
- risk factors
- feature selection
- machine learning methods
- data mining
- computed tomography
- computer aided
- svm classification
- support vector
- data analysis
- learning algorithm
- medical experts
- image reconstruction
- information criterion
- machine learning algorithms
- active learning
- text classification