| Survey of XAI in digital pathology M Pocevičiūtė, G Eilertsen, C Lundström Artificial intelligence and machine learning for digital pathology: state-of …, 2020 | 55 | 2020 |
| Generalisation effects of predictive uncertainty estimation in deep learning for digital pathology M Pocevičiūtė, G Eilertsen, S Jarkman, C Lundström Scientific Reports 12 (1), 8329, 2022 | 21 | 2022 |
| Generalization of deep learning in digital pathology: experience in breast cancer metastasis detection S Jarkman, M Karlberg, M Pocevičiūtė, A Bodén, P Bándi, G Litjens, ... Cancers 14 (21), 5424, 2022 | 13 | 2022 |
| Unsupervised anomaly detection in digital pathology using GANs M Pocevičiūtė, G Eilertsen, C Lundström 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1878-1882, 2021 | 12 | 2021 |
| Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance M Pocevičiūtė, G Eilertsen, S Garvin, C Lundström International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 2 | 2023 |
| Spatial uncertainty aggregation for false negatives detection in breast cancer metastases segmentation M Pocevičiūtė, G Eilertsen, C Lundström Medical Imaging 2023: Digital and Computational Pathology 12471, 216-223, 2023 | 1 | 2023 |
| Benefits of spatial uncertainty aggregation for segmentation in digital pathology M Pocevičiūtė, G Eilertsen, C Lundström Journal of Medical Imaging 11 (1), 017501-017501, 2024 | | 2024 |
| Generalisation and reliability of deep learning for digital pathology in a clinical setting M Pocevičiūtė Linköping University Electronic Press, 2023 | | 2023 |
