【AI-for-Medical-Prognosis】

★Project1:Build and Evaluate a Linear Risk model

1. Data preprocessing
   -Log transformations
   -Standardization
   
2. Basic Risk Models
   -Logistic Regression
   -C-index
   -Interactions Terms
   

★Project2:Risk Models Using Tree-based Models

1. Dealing with Missing Data
   -Complete Case Analysis
   -Imputation
   
2. Decision Trees
   -Evaluation
   -Regularization
   3.Random Forests
   -Hyperparameter Tuning
   

★Project3:Survival Estimates that Varies with Time

1. Censored Data
   
2. Kaplan-Meier Estimates
   
3. Subgroup Analysis
   

★Projects4:Cox Proportional Hazards and Random Survival Forests

1. Cox Proportional Hazards
   -Data Preprocessing for Cox Models
   
2. Random Survival Forests
   -Permutation Methods for Interpretation