A Novel Ensemble-based Classifier for Detecting the COVID-19 Disease for Infected Patients.
Prabhdeep SinghRajbir KaurKiran Deep SinghGaurav DhimanPublished in: Inf. Syst. Frontiers (2021)
Keyphrases
- infectious disease
- ensemble learning
- classifier ensemble
- training data
- ensemble classifier
- multiple classifiers
- multiple sclerosis
- medical doctors
- training set
- early diagnosis
- final classification
- individual classifiers
- feature selection
- emergency department
- patient groups
- clinical studies
- cardiovascular disease
- liver disease
- weak learners
- disease progression
- random forests
- ensemble methods
- combining classifiers
- amyotrophic lateral sclerosis
- chronic disease
- survival prediction
- chronic obstructive pulmonary disease
- decision tree classifiers
- learning algorithm
- accurate classifiers
- neural network
- random forest
- public health
- clinically relevant
- diagnostic tool
- cancer patients
- feature set
- bias variance decomposition
- feature space
- multiple classifier systems
- decision trees
- weak classifiers
- diabetic patients
- base classifiers
- classifier combination
- training samples
- class labels
- electronic medical record
- svm classifier
- fold cross validation
- majority voting
- disease diagnosis
- medical diagnosis
- white matter
- lung cancer
- support vector machine
- clinical trials
- medical practitioners
- support vector
- binary classification problems