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Found 5 papers, 4 papers with code
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed
Failure detection in automated image classification is a critical safeguard for clinical deployment.
Algorithmic encoding of protected characteristics in image-based models for disease detection
We explore test set resampling, transfer learning, multitask learning, and model inspection to assess the relationship between the encoding of protected characteristics and disease detection performance across subgroups.
Active label cleaning for improved dataset quality under resource constraints
Imperfections in data annotation, known as label noise, are detrimental to the training of machine learning models and have an often-overlooked confounding effect on the assessment of model performance.
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Chest radiography has been a recommended procedure for patient triaging and resource management in intensive care units (ICUs) throughout the COVID-19 pandemic.
Training Variational Networks with Multi-Domain Simulations: Speed-of-Sound Image Reconstruction
In this work, we present for the first time a VN solution for a pulse-echo SoS image reconstruction problem using diverging waves with conventional transducers and single-sided tissue access.
