Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound.

Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based solutions for the assisted diagnosis of lung diseases. While existing works focus on CT scans, this paper studies the application of DL techniques for the analysis of lung ultrasonography (LUS) images. Specifically, we present a novel fully-annotated dataset of LUS images collected from several Italian hospitals, with labels indicating the degree of disease severity at a frame-level, video-level, and pixel-level (segmentation masks).

Assessment tool for the instructional design of simulation-based team training courses: the ID-SIM.

Introduction: To achieve an expert performance of care teams, adequate simulation-based team training courses with an effective instructional design are essential. As the importance of the instructional design becomes ever more clear, an objective assessment tool would be valuable for educators and researchers. Therefore, we aimed to develop an evidence-based and objective assessment tool for the evaluation of the instructional design of simulation-based team training courses.