Severity prediction in COVID-19 patients using clinical markers and explainable artificial intelligence: A stacked ensemble machine learning approach.
Krishnaraj ChadagaSrikanth PrabhuNiranjana SampathilaRajagopala ChadagaPublished in: Intell. Decis. Technol. (2023)
Keyphrases
- machine learning
- artificial intelligence
- clinical data
- disease progression
- patient data
- clinical trials
- clinical diagnosis
- ensemble classifier
- clinically relevant
- prediction accuracy
- medical data
- patient records
- outcome prediction
- clinical information
- neural network ensemble
- medical treatment
- ensemble methods
- medical records
- intensive care
- intensive care unit
- computational intelligence
- natural language processing
- learning algorithm
- medical experts
- clinical setting
- cardiovascular disease
- feature selection
- computer science
- neurological disorders
- medical doctors
- heart disease
- patient care
- therapy planning
- knowledge representation
- machine learning methods
- cancer patients
- patient groups
- traumatic brain injury
- blood glucose
- medical domain
- clinical practice
- ensemble learning
- clinical decision support
- cancer treatment
- clinical studies
- diabetic patients
- multiple sclerosis
- chronic hepatitis
- predictive modeling
- ischemic stroke
- medical center
- survival prediction
- acute myocardial infarction
- diabetes mellitus
- chronic disease
- blood pressure
- medical knowledge
- medical diagnosis
- expert systems
- electronic medical record
- home care
- survival data
- treatment planning
- health information systems
- breast cancer
- mr images