| Early Detection of Sepsis Induced Deterioration Using Machine Learning F Dal Canton, VM Quinten, MA Wiering Artificial Intelligence: 30th Benelux Conference, BNAIC 2018,‘s …, 2019 | 1 | 2019 |
| Early Detection of Sepsis Induced Deterioration with First 48-hour ECG, Plethysmograph, and Respiratory Rate Biosignals Using Machine Learning Models F Dal Canton | 1 | 2018 |
| Mammary duct detection using self-supervised encoders S Doyle, F Dal Canton, J Wesseling, CI Sánchez, J Teuwen Medical Imaging 2022: Computer-Aided Diagnosis 12033, 229-232, 2022 | | 2022 |
| Deep learning applied on resection specimen tissue slides of'pure'ductal carcinoma in situ predicts ipsilateral invasive breast cancer recurrence S Doyle, F Dal Canton, T Koostra, M van Seijen, E Groen, E Gavves, ... CANCER RESEARCH 82 (4), 2022 | | 2022 |
| Multiple-instance learning for assessing prognosis of ductal carcinoma in situ F Dal Canton, M van Seijen, E Groen, H Horlings, E Lips, E Gavves, ... VIRCHOWS ARCHIV 479 (SUPPL 1), S61-S61, 2021 | | 2021 |
| Deep Learning for Predicting Invasive Recurrence of Ductal Carcinoma in Situ: Leveraging Histopathology Images and Clinical Features S Doyle, EH Lips, E Marcus, L Mulder, YH Liu, F Dal Canton, T Kootstra, ... | | |
Marco WieringInstitute of Artificial Intelligence and Cognitive Engineering, University of GroningenVerified email at rug.nl
