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Figure 1

From: Data valuation for medical imaging using Shapley value and application to a large-scale chest X-ray dataset

Figure 1

Overview of our method. (a) The input data were chest X-ray images and their corresponding labels (1 for pneumonia and 0 for no pneumonia) from ChestX-ray14 dataset9. (b) To compute data Shapley values for the training data, we first extracted feature vectors from a pre-trained convolutional neural network (CNN), CheXNet36. Next, we applied TMC-Shapley17 to approximate the Shapley value of each training datum, where the supervised learning algorithm was logistic regression, and the predictor performance score was prediction accuracy for pneumonia.

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