Speaker
Description
Computational pathology has made tremendous progress on dedicated datasets in the past years. However, currently such algorithms are still not used routinely for diagnostics in the clinics. There is still a large gap between research and clinics and the factors that contribute to this, such as the focus on reproducing subjective scores and the large variance in performance depending on the data source. One important goal is, therefore, to overcome subjective scores by introducing objective endpoints, as well as developing quantifiable and objective metrics based on specialised microscopy types. In order to further close the gap, robustness to domain shifts between datasets and generalizability, as well as measures of uncertainty to defer uncertain decisions are important topics.
| I want to give a Lightning Talk | yes |
|---|
