Papers › Machine Learning for Exam Triage

Machine Learning for Exam Triage

30 Apr 2018arXiv:1805.00503archive 2025-07-28

Xinyu Guan, Jessica Lee, Peter Wu, Yue Wu

In this project, we extend the state-of-the-art CheXNet (Rajpurkar et al. [2017]) by making use of the additional non-image features in the dataset. Our model produced better AUROC scores than the original CheXNet.

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Holmeswww/CheXNetPP officialmentioned in paperpytorch report

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Tasks

BIG-bench Machine Learning

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Methods

1x1 Convolution Average Pooling Batch Normalization CheXNet Concatenated Skip Connection Convolution Dense Block Dense Connections Dropout Global Average Pooling Kaiming Initialization Max Pooling ReLU Softmax

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