Machine Learning for Exam Triage
Xinyu Guan, Jessica Lee, Peter Wu, Yue Wu
2018-04-30BIG-bench Machine Learning
Abstract
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.
Related Papers
(1,1)-Cluster Editing is Polynomial-time Solvable2022-10-14AnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks2022-10-14Discover the Mysteries of the Maya: Selected Contributions from the Machine Learning Challenge & The Discovery Challenge Workshop at ECML PKDD 20212022-08-05Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity2022-08-05Explanation of Machine Learning Models of Colon Cancer Using SHAP Considering Interaction Effects2022-08-05Machine Learning and Bioinformatics for Diagnosis Analysis of Obesity Spectrum Disorders2022-08-05A Lightweight Machine Learning Pipeline for LiDAR-simulation2022-08-05Evolutionary bagging for ensemble learning2022-08-04