Uncertainty, robustness and safety in artificial intelligence, with applications in healthcare
| Authors | |
|---|---|
| Supervisors | |
| Cosupervisors |
|
| Award date | 27-09-2022 |
| Number of pages | 83 |
| Organisations |
|
| Abstract | My thesis includes 4 independent chapters, and their topics are novel uncertainty quantification methods for medical image segmentation and reconstruction, a robust deep model for survival analysis, and a novel gray box adversarial defense. The thesis has a mix of theoretical and empirical results, and contains two applications in healthcare, which are medical image analysis and survival analysis. |
| Document type | PhD thesis |
| Language | English |
| Downloads | |
| Permalink to this page | |