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Interpretable Machine Learning Approaches to Prediction of Chronic Homelessness., , , and . CoRR, (2020)A survey of the impact of self-supervised pretraining for diagnostic tasks in medical X-ray, CT, MRI, and ultrasound., , and . BMC Medical Imaging, 24 (1): 79 (December 2024)Accurate assessment of the lung sliding artefact on lung ultrasonography using a deep learning approach., , , , , , , , , and 6 other author(s). Comput. Biol. Medicine, (2022)Interpretable machine learning approaches to prediction of chronic homelessness., , , and . Eng. Appl. Artif. Intell., (2021)Dream to Explore: Adaptive Simulations for Autonomous Systems., , , , , and . CoRR, (2021)Automatic segmentation of the carotid artery and internal jugular vein from 2D ultrasound images for 3D vascular reconstruction., , , , , and . Int. J. Comput. Assist. Radiol. Surg., 15 (11): 1835-1846 (2020)Improving central line needle insertions using in-situ vascular reconstructions., , , , , and . Comput. methods Biomech. Biomed. Eng. Imaging Vis., 9 (4): 363-369 (2021)Univariate Long-Term Municipal Water Demand Forecasting., , and . CoRR, (2021)Exploring the Utility of Self-Supervised Pretraining Strategies for the Detection of Absent Lung Sliding in M-Mode Lung Ultrasound., , , , and . CVPR Workshops, page 3077-3086. IEEE, (2023)Self-Supervised Pretraining Improves Performance and Inference Efficiency in Multiple Lung Ultrasound Interpretation Tasks., , , and . CoRR, (2023)