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Semi-Supervised Active Learning for COVID-19 Lung Ultrasound Multi-symptom Classification
2020
2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI)
Ultrasound (US) is a non-invasive yet effective medical diagnostic imaging technique for the COVID-19 global pandemic. However, due to complex feature behaviors and expensive annotations of US images, it is difficult to apply Artificial Intelligence (AI) assisting approaches for the lung's multi-symptom (multi-label) classification. To overcome these difficulties, we propose a novel semi-supervised Two-Stream Active Learning (TSAL) method to model complicated features and reduce labeling costs
doi:10.1109/ictai50040.2020.00191
fatcat:aixm52wfybe4ngb4umnjk4gjqe