Search Results for author: Jared A. Dunnmon

Found 5 papers, 3 papers with code

No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems

1 code implementation NeurIPS 2020 Nimit S. Sohoni, Jared A. Dunnmon, Geoffrey Angus, Albert Gu, Christopher Ré

As the subclass labels are frequently unavailable, models trained using only the coarser-grained class labels often exhibit highly variable performance across different subclasses.

General Classification Image Classification

Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset

no code implementations15 Oct 2020 Siyi Tang, Amirata Ghorbani, Rikiya Yamashita, Sameer Rehman, Jared A. Dunnmon, James Zou, Daniel L. Rubin

In this study, we used data Shapley, a data valuation metric, to quantify the value of training data to the performance of a pneumonia detection algorithm in a large chest X-ray dataset.

Data Valuation Pneumonia Detection

Assessing Robustness to Noise: Low-Cost Head CT Triage

no code implementations17 Mar 2020 Sarah M. Hooper, Jared A. Dunnmon, Matthew P. Lungren, Sanjiv Sam Gambhir, Christopher Ré, Adam S. Wang, Bhavik N. Patel

We then show that the trained model is robust to reduced tube current and fewer projections, with the AUROC dropping only 0. 65% for images acquired with a 16x reduction in tube current and 0. 22% for images acquired with 8x fewer projections.

Computed Tomography (CT) Image Classification +1

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