Transcription of Machine Learning for Survival Analysis
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Machine Learning for Survival Analysis
Machine Learning for Survival Analysis Chandan K. Reddy Yan Li Dept. of Computer Science Dept. of Computational Medicine Virginia Tech and Bioinformatics ~reddy Univ. of Michigan, Ann Arbor 1. Tutorial Outline Basic Concepts Statistical Methods Machine Learning Methods Related Topics 2. Tutorial Outline Basic Concepts Statistical Methods Machine Learning Methods Related Topics 3. Healthcare Demographics Comorbodities Laboratory Procedures Medications Age Hypertension Hemoglobin Hemodialysis ACE inhibitor Gender Diabetes Blood count Contrast dye Dopamine Race CKD Glucose Catheterization Milrinone Event IMPACT. Prediction Lower healthcare costs Improve quality of life Model Event of Interest : Rehospitalization; Disease recurrence; Cancer Survival Outcome: Likelihood of hospitalization within t days of discharge 4.
6 Goal of survival analysis: To estimate the time to the event of interest 6 Ýfor a new instance with feature predictors denoted by : Ý. Problem Statement For a given instance E, represented by a triplet : : Ü, Ü, Ü ;. : Üis the feature vector; Ü Üis the binary event indicator, i.e., Ü 1 for an uncensored instance and Ü Ü0 for a censored instance;
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