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cs.LG2022
Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation
Thomas Buddenkotte, Lorena Escudero Sanchez, Mireia Crispin-Ortuzar +6
Uncertainty quantification in automated image analysis is highly desired in many applications. Typically, machine learning models in classification or segmentation are only develop…
cs.LG2020★ 1k cited
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Michael Roberts, Derek Driggs, Matthew Thorpe +13
Machine learning methods offer great promise for fast and accurate detection and prognostication of COVID-19 from standard-of-care chest radiographs (CXR) and computed tomography (…