Model uncertainty in computational pathology with Milda Poceviciute
Channel: Aleksandra Zuraw Digital Pathology Place
Date: 2022-11-04

We all look up the weather forecast every day, although we know they are not that certain - we accept it, are fine with it and often secretly hope that the predictions don't come true.

But how should we deal with computational pathology model uncertainty? How much uncertainty can we afford? How do we deal with different uncertainty levels and when should we say "enough is enough" and disregard the prediction altogether?

This talk's expert Milda Poceviciute from the Linköping University will walk you through the nuances of this concept. She will explain:

- What uncertainty is.
- Why it is important to analyze uncertainty.
- What it is used for.
- Uncertainty vs Attention vs probability of a model
- What are the applications of uncertainty analysis in pathology. 

So Listen in and comment if you like it or you have any more questions!

This talk's resources:
- Survey of XAI in Digital Pathology:
https://link.springer.com/chapter/10.1007/978-3-030-50402-1_4

- Generalisation effects of predictive uncertainty estimation in deep learning for digital pathology:
https://www.nature.com/articles/s41598-022-11826-0