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20192024
most citedCommon pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

1k citations

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Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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2 papers · 1 filter

cs.LG2024★ 1 cited

Imbalanced Graph-Level Anomaly Detection via Counterfactual Augmentation and Feature Learning

Zitong Wang, Xuexiong Luo, Enfeng Song +2

Graph-level anomaly detection (GLAD) has already gained significant importance and has become a popular field of study, attracting considerable attention across numerous downstream…

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 (…