Machine Learning for Exam Triage

04/30/2018

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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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Machine Learning for Exam Triage

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Finetuning for Sarcasm Detection with a Pruned Dataset

Dark patterns in e-commerce: a dataset and its baseline evaluations

Revisiting Deep Learning for Variable Type Recovery

Painting Outside the Box: Image Outpainting with GANs

Dropout against Deep Leakage from Gradients

Response to Comment on "All-optical machine learning using diffractive deep neural networks"

Machine Learning for Exam Triage

Related Research

Assessing the Effectiveness of GPT-3 in Detecting False Political Statements: A Case Study on the LIAR Dataset

Finetuning for Sarcasm Detection with a Pruned Dataset

Dark patterns in e-commerce: a dataset and its baseline evaluations

Revisiting Deep Learning for Variable Type Recovery

Painting Outside the Box: Image Outpainting with GANs

Dropout against Deep Leakage from Gradients

Response to Comment on "All-optical machine learning using diffractive deep neural networks"