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Found 5 papers, 1 papers with code
Improved Multimodal Fusion for Small Datasets with Auxiliary Supervision
We validate the proposed approaches on prostate cancer diagnosis from paired histopathology imaging and tabular clinical features.
Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models
CL based pretraining with NST significantly improves DL classification performance, helps the model generalize well (transferable from EyePACS to UIC data), and allows training with small, annotated datasets, therefore reducing ground truth annotation burden of the clinicians.
Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentation
Although various methods such as domain adaptation and domain generalization have evolved to combat this challenge, learning robust and generalizable representations is core to medical image understanding, and continues to be a problem.
Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset
In this study, we used data Shapley, a data valuation metric, to quantify the value of training data to the performance of a pneumonia detection algorithm in a large chest X-ray dataset.
Analysis Of Multi Field Of View Cnn And Attention Cnn On H&E Stained Whole-slide Images On Hepatocellular Carcinoma
Determination of the tile size affects the performance of the algorithms since small field of view can not capture the information on a larger scale and large field of view can not capture the information on a cellular scale.
