Machine-learning-assisted spontaneous Raman spectroscopy classification and feature extraction for the diagnosis of human laryngeal cancer.
Zheng LiZhongqiang LiQing ChenJian ZhangMichael E. DunhamAndrew J. McWhorterJi-Ming FengYanping LiShaomian YaoJian XuPublished in: Comput. Biol. Medicine (2022)
Keyphrases
- feature extraction
- machine learning
- pattern recognition
- feature selection
- pattern classification
- cancer diagnosis
- machine learning methods
- feature vectors
- feature space
- image classification
- support vector machine svm
- supervised learning
- machine learning algorithms
- supervised machine learning
- text classification
- feature extraction and classification
- preprocessing
- support vector machine
- decision trees
- extracted features
- x ray
- machine learning approaches
- feature set
- image processing
- bladder cancer
- neural network
- clinical diagnosis
- infrared
- support vector
- dimension reduction
- cancer classification
- breast cancer diagnosis
- supervised classification
- clinically relevant
- model selection
- kernel principal component analysis
- feature representation
- texture analysis
- microarray data
- active learning
- high dimensional
- face recognition
- learning algorithm
- data mining