Predicting patients with Parkinson's disease using Machine Learning and ensemble voting technique.
Shawki SalehBouchaib CherradiOussama El GannourSoufiane HamidaOmar BouattanePublished in: Multim. Tools Appl. (2024)
Keyphrases
- machine learning
- voting schemes
- multiple sclerosis
- early diagnosis
- medical doctors
- learning algorithm
- emergency department
- weighted voting
- feature selection
- cardiovascular disease
- amyotrophic lateral sclerosis
- patient groups
- diabetic patients
- clinical studies
- majority voting
- ensemble methods
- clinically relevant
- disease progression
- deep brain stimulation
- diagnostic tool
- chronic disease
- machine learning methods
- survival prediction
- information extraction
- chronic obstructive pulmonary disease
- clinical data
- data mining
- machine learning algorithms
- training data
- natural language processing
- random forest
- liver disease
- infectious disease
- neural network
- medical treatment
- medical practice
- decision trees
- medical data
- caudate nucleus
- cancer patients
- training set
- magnetic resonance images
- diabetes mellitus
- ensemble learning
- support vector machine
- computer aided
- clinical trials