Feature Extraction
PyTorch
English
moozy
pathology
computational-pathology
digital-pathology
foundation-model
whole-slide-image
vision-transformer
self-supervised-learning
slide-encoder
case-encoder
histopathology
medical-imaging
multiple-instance-learning
slide-level-representation
patient-level-representation
multi-task-learning
survival-analysis
cancer
oncology
tissue-classification
mutation-prediction
TCGA
CPTAC
transformer
Eval Results (legacy)
| task_type: survival | |
| organ: uterus, nos | |
| sample_col: case_id | |
| task_col: DFI | |
| event_col: DFI_event | |
| time_col: DFI_days | |
| label_dict: | |
| 0: Quartile 1, Event 0 | |
| 1: Quartile 2, Event 0 | |
| 2: Quartile 3, Event 0 | |
| 3: Quartile 4, Event 0 | |
| 4: Quartile 1, Event 1 | |
| 5: Quartile 2, Event 1 | |
| 6: Quartile 3, Event 1 | |
| 7: Quartile 4, Event 1 | |
| metrics: | |
| - cindex | |