Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts.
Georgios BaskozosAndreas C. ThemistocleousHarry L. HebertMathilde M. V. PascalJishi JohnBrian C. CallaghanHelen LaycockYelena GranovskyGeert CrombezDavid YarnitskyAndrew S. C. RiceBlair H. SmithDavid L. H. BennettPublished in: BMC Medical Informatics Decis. Mak. (2022)
Keyphrases
- cross sectional
- machine learning models
- spam filtering
- machine learning algorithms
- machine learning
- machine learning approaches
- diabetic patients
- real world
- classification accuracy
- decision trees
- feature extraction
- support vector
- learning models
- data sets
- cross section
- mri data
- blood vessels
- training set
- text classification
- supervised learning
- learning problems
- classification algorithm
- training data
- support vector machine
- image segmentation
- feature space