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Found 5 papers, 2 papers with code
Interpretable histopathology-based prediction of disease relevant features in Inflammatory Bowel Disease biopsies using weakly-supervised deep learning
Finally, we identified several cell level features indicative of disease severity in CD and UC.
Coupling Deep Imputation with Multitask Learning for Downstream Tasks on Genomics Data
Genomics data such as RNA gene expression, methylation and micro RNA expression are valuable sources of information for various clinical predictive tasks.
Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data
The presence of basal cells is the most accepted biomarker for benign glandular tissue and the absence of basal cells is a strong indicator of acinar prostatic adenocarcinoma, the most common form of prostate cancer.
A Deep Learning Framework for Automatic Diagnosis in Lung Cancer
The performance of the developed deep learning framework was evaluated on fully annotated TMA cores from 178 patients reaching pixel-wise precision of 0. 80 and recall of 0. 86.
Multi-Resolution Networks for Semantic Segmentation in Whole Slide Images
Digital pathology provides an excellent opportunity for applying fully convolutional networks (FCNs) to tasks, such as semantic segmentation of whole slide images (WSIs).
