APPLYING LATENT CLASS CLUSTER ANALYSIS AND DATA MINING METHODS TO IDENTIFY CLASSES OF CHRONIC FATIGUE SYNDROME PATIENTS THAT ARE PREDICTIVE OF TREATMENT SUCCESS
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- - Academic And Stem
- - Accounting, Finance And Commerce
- - Archaeological Sciences And History
- - Biological And Life Sciences
- - Botanical Studies And Agriculture
- - Chemical Sciences And Chemistry
- - Computer Science & Engineering And It
- - Construction Management And Civil Engineering
- - Crime, Law And Forensics
- - Environmental Studies: Ecology, Conservation, And Management
- - Geological And Planetary Sciences
- - Healthcare, Medicine And Clinical Studies
- - Linguistics And Language Science
- - Mechanical, Manufacturing, And Design Engineering
- - Media And Journalism
- - Mental Health And Psychological Studies
- - Nutritional And Food Science
- - Pharmacy, Pharmacology And Pharmaceutical Sciences
- - Philosophy And Ethics
- - Physics: Science And Engineering
- - Political Studies
- - Probability, Statistics And Mathematics
- - Research In Education: Pedagogy And Learning Processes
- - Society, Culture And Social Studies
- - Systems Engineering: Communication, Electrical And Elecronics
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APPLYING LATENT CLASS CLUSTER ANALYSIS AND DATA MINING METHODS TO IDENTIFY CLASSES OF CHRONIC FATIGUE SYNDROME PATIENTS THAT ARE PREDICTIVE OF TREATMENT SUCCESS