##### Department of Mathematics,

University of California San Diego

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### Department Colloquium

## Denise Rava - Graduate Student

#### UC San Diego

## Additive Hazards Model: Explained Variation and a Neural Network extension

##### Abstract:

Prognostic models in survival analysis are aimed at understanding the relationship between patients' covariates and the distribution of survival time. Traditionally, semi-parametric models, such as the Cox model and the Additive Hazards model, have been assumed. In this talk I will derive a measure of explained variation under the Additive Hazards model showing its properties. Moreover I will describe the development of a new flexible method for survival prediction: DeepHazard, a neural network for time-varying risks. I will show its performance on popular real datasets.

Host: Laura Stevens

### March 9, 2021

### 3:00 PM

### Location: https://ucsd.zoom.us/j/94147847821

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