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Course: AI for Medical Prognosis . Click here to go back.
- Course 2 Intro with Andrew and Pranav
- Prerequisites and Learning Outcomes
- Medical Prognosis
- Examples of Prognostic Tasks
- Atrial fibrillation
- Liver Disease Mortality
- Risk of heart disease
- Risk Score Computation
- Evaluating Prognostic Models
- Concordant Pairs, Risk Ties, Permissible Pairs
- C-Index
- Decision trees for prognosis
- Decision trees
- Dividing the input space
- Building a decision tree
- How to fix overfitting
- Survival Data
- Different distributions
- Missing Data example
- Missing completely at random
- Missing at random
- Missing not at random
- Imputation
- Mean Imputation
- Regression Imputation
- Calculate Imputed Values
- Survival models
- Survival Function
- Valid survival functions
- Collecting Time Data
- When a stroke is not observed
- Heart Attack Data
- Right censoring
- Estimating the survival function
- Died immediately, or never die
- Somewhere in-between
- Using censored data
- Chain rule of conditional probability
- Deriving Survival
- Calculating Probabilities from the Data
- Comparing Estimates
- Kaplan Meier Estimate
- Hazard Functions
- Hazard
- Survival to hazard
- Cumulative Hazard
- Individualized Predictions
- Relative risk
- Ranking patients by risk
- Individual vs. baseline hazard
- Smoker vs. non-smoker
- Effect of age on hazard
- Risk factor increase per unit increase in a variable
- Risk Factor Increase or Decrease
- Intro to Survival Trees
- Survival tree
- Nelson Aalen estimator
- Comparing risks of patients
- Mortality score
- Evaluation of Survival Model
- Permissible and Non-Permissible Pairs
- Possible Permissible Pairs
- Example of Harrell's C-Index
- Example of Concordant Pairs
- Week 4 Summary
- Congratulations!