Combining multiple contrasts for improving machine learning-based classification of cervical cancers with a low-cost point-of-care Pocket colposcope.
Mercy Nyamewaa AsieduErica SkerrettGuillermo SapiroNirmala RamanujamPublished in: EMBC (2020)
Keyphrases
- combining multiple
- machine learning
- low cost
- multiple classifiers
- machine learning methods
- supervised learning
- text classification
- combining classifiers
- pattern recognition
- support vector machine
- machine learning algorithms
- classification accuracy
- decision trees
- feature selection
- support vector
- feature space
- individual classifiers
- cancer classification
- cluster ensemble
- gene expression profiles
- cancer diagnosis
- text mining
- cancer detection
- classifier combination
- support vector machine svm
- fusion methods
- prostate cancer
- gene selection
- high dimensionality
- training samples
- unsupervised learning
- feature set
- learning algorithm