| Abstrakt: |
A recent study conducted at the Cleveland Clinic explored the use of interpretable machine learning models to predict the conversion to neurological diseases. The researchers compiled a dataset of patients diagnosed with Alzheimer's disease, amyotrophic lateral sclerosis, multiple sclerosis, or Parkinson's disease, along with matched controls. The models achieved varying levels of accuracy in predicting the diseases at different timepoints prior to diagnosis. The study concluded that electronic medical records contain valuable information that can be used for risk stratification of neurological disorders. [Extracted from the article] |
