The Effect of Counterfactuals on Reading Chest X-rays
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Abstract (arXiv)
This study evaluates the effect of counterfactual explanations on the interpretation of chest X-rays. We conduct a reader study with two radiologists assessing 240 chest X-ray predictions to rate their confidence that the model's prediction is correct using a 5 point scale. Half of the predictions are false positives. Each prediction is explained twice, once using traditional attribution methods and once with a counterfactual explanation. The overall results indicate that counterfactual explanations allow a radiologist to have more confidence in true positive predictions compared to traditional approaches (0.15±0.95 with p=0.01) with only a small increase in false positive predictions (0.04±1.06 with p=0.57). We observe the specific prediction tasks of Mass and Atelectasis appear to benefit the most compared to other tasks.
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References · 4
- 2017Axiomatic Attribution for Deep Networkscited by 3,384
- 2014Striving for Simplicity: The All Convolutional Netcited by 990
- 2017Right for the Right Reasons: Training Differentiable Models by Constraining their Explanationscited by 294
- 2021TorchXRayVision: A library of chest X-ray datasets and modelscited by 131
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