Abstract Purpose To review eXplainable Artificial Intelligence/(XAI) methods available for
medical imaging/(MI). Method A scoping review was conducted following the Joanna Briggs …

Background: Chest X-ray (CXR) remains the standard imaging modality in postoperative
care after non-cardiac thoracic surgery. Lung ultrasound (LUS) showed promising results in …

Objective. Ultrasound is extensively utilized as a convenient and cost-effective method in
emergency situations. Unfortunately, the limited availability of skilled clinicians in emergency …

Self-supervised pretraining has been observed to improve performance in supervised
learning tasks in medical imaging. This study investigates the utility of self-supervised …

Background Lung ultrasound has been increasingly used in the last years for the
assessment of patients with respiratory diseases; it is considered a simple technique, now …

Deep learning (DL) models for medical image classification frequently struggle to generalize
to data from outside institutions. Additional clinical data are also rarely collected to …

Introduction: Point-of-care ultrasound has become a universal practice, employed by
physicians across various disciplines, contributing to diagnostic processes and decision …

Self-supervised learning (SSL) is one strategy for addressing the paucity of labelled data in
medical imaging by learning representations from unlabelled images. Contrastive and non …

Context: Neonatal lung ultrasound is emerging as a useful clinical tool for the assessment of
lung anatomy and management of various lung pathologies. In this review, we summarize …

Background Rapid evaluation for pneumothorax is a common clinical priority. Although lung
ultrasound (LUS) often is used to assess for pneumothorax, its diagnostic accuracy varies …