28 citations · 52 across the 6 of their papers we have counts for
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eess.IV2021
Robust Weakly Supervised Learning for COVID-19 Recognition Using Multi-Center CT Images
Qinghao Ye, Yuan Gao, Weiping Ding +8
The world is currently experiencing an ongoing pandemic of an infectious disease named coronavirus disease 2019 (i.e., COVID-19), which is caused by the severe acute respiratory sy…
cs.LG2021★ 7 cited
Explainable AI For COVID-19 CT Classifiers: An Initial Comparison Study
Qinghao Ye, Jun Xia, Guang Yang
Artificial Intelligence (AI) has made leapfrogs in development across all the industrial sectors especially when deep learning has been introduced. Deep learning helps to learn the…
cs.AI2021★ 15 cited
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond
Guang Yang, Qinghao Ye, Jun Xia
Explainable Artificial Intelligence (XAI) is an emerging research topic of machine learning aimed at unboxing how AI systems' black-box choices are made. This research field inspec…