Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

Traditional health systems mostly rely on rules created by experts to offer adaptive
interventions to patients. However, with recent advances in artificial intelligence (AI) and …

Purpose To evaluate the trustworthiness of saliency maps for abnormality localization in
medical imaging. Materials and Methods Using two large publicly available radiology …

Medical imaging refers to several different technologies that are used to view the human
body to diagnose, monitor, or treat medical conditions. It requires significant expertise to …

Artificial intelligence (AI) has prom-ise for automating the diagnosis of diseases from medical
imaging, with some deep learning models demonstrating performance comparable to that of …

Twitter is a social media site where people post their personal experiences, opinions, and
news. Due to the ubiquitous real-time data availability, many rescue agencies monitor this …

Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less
attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) …

Social media like Twitter provide a common platform to share and communicate personal
experiences with other people. People often post their life experiences, local news, and …

In spite of an exponential increase in the volume of medical data produced globally, much of
these data are inaccessible to those who might best use them to develop improved health …

Accurate segmentation of the pneumothorax from chest X-ray images is of considerable
significance for the diagnosis in the emergency department. Recently, deep learning …