Question

a hospital wants to predict patient readmission risk based on historical patient data, including age, medical history, current conditions, and whether they were readmitted within 30 days. supervised learning with historical outcomes unsupervised learning to group patients no machine learning needed - use traditional statistics

Explanation:

The hospital wants to predict patient readmission risk using historical data with known outcomes (whether readmitted or not). Supervised learning is used when there are labeled data (in this case, the readmission status is the label) to train a model for prediction. Unsupervised learning is for finding patterns in un - labeled data like grouping patients without a specific target variable. Traditional statistics might not be as effective for complex prediction tasks based on multiple factors as machine - learning algorithms in supervised learning.

Answer:

Supervised learning with historical outcomes