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Found 5 papers, 3 papers with code
Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation
Feature attribution methods identify which features of an input most influence a model's output.
Benchmarking saliency methods for chest X-ray interpretation
Saliency methods, which produce heat maps that highlight the areas of the medical image that influence model prediction, are often presented to clinicians as an aid in diagnostic decision-making.
Learning Invariant Representations with Missing Data
Enforcing such independencies requires nuisances to be observed during training.
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management
Recent advances in Natural Language Processing (NLP), and specifically automated Question Answering (QA) systems, have demonstrated both impressive linguistic fluency and a pernicious tendency to reflect social biases.
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
We release a development dataset, which contains board-certified radiologist annotations for 500 radiology reports from the MIMIC-CXR dataset (14, 579 entities and 10, 889 relations), and a test dataset, which contains two independent sets of board-certified radiologist annotations for 100 radiology reports split equally across the MIMIC-CXR and CheXpert datasets.
