Search Results for author:
Found 4 papers, 3 papers with code
Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification
To aid radiological reading, we propose an auxiliary task-based multiple instance learning approach (ATMIL) for MM classification with the ability to localize sites of disease.
Transductive image segmentation: Self-training and effect of uncertainty estimation
It focuses on the quality of predictions made on the unlabeled data of interest when they are included for optimization during training, rather than improving generalization.
Algorithmic encoding of protected characteristics in image-based models for disease detection
We explore test set resampling, transfer learning, multitask learning, and model inspection to assess the relationship between the encoding of protected characteristics and disease detection performance across subgroups.
Risk of Bias in Chest Radiography Deep Learning Foundation Models
Purpose: To analyze a recently published chest radiography foundation model for the presence of biases that could lead to subgroup performance disparities across biological sex and race.
