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Literature and educational tools generated from Project Deep Breathe to further understanding of lung ultrasound, AI and their intersection.

Resources

1. "Enhancing Annotation Efficiency with Machine Learning: Automated Partitioning of a Lung Ultrasound Dataset by View", Diagnostics. Sep 2022

2. "Accurate assessment of the lung sliding artefact on lung ultrasonography using a deep learning approach", Computers in Biology and Medicine. Aug 2022

3. "Automation of Lung Ultrasound Interpretation via Deep Learning for the Classification of Normal versus Abnormal Lung Parenchyma: A Multicenter Study", Diagnostics. November 2021

4. "Development of a convolutional neural network to differentiate among the etiology of similar appearing pathological B lines on lung ultrasound: a deep learning study", BMJ Open. Feb 2021

5. "Introducing medical students to deep learning through image labelling: a new approach to meet calls for greater artificial intelligence fluency among medical trainees", CMEJ. Oct 2022

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