Classification of Cervical Spine Fracture and Dislocation Using Refined Pre-Trained Deep Model and Saliency Map.

Cervical spine (CS) fractures or dislocations are medical emergencies that may lead to more serious consequences, such as significant functional disability, permanent paralysis, or even death. Therefore, diagnosing CS injuries should be conducted urgently without any delay. This paper proposes an accurate computer-aided-diagnosis system based on deep learning (AlexNet and GoogleNet) for classifying CS injuries as fractures or dislocations.

Cross-sectional study of Middle East respiratory syndrome coronavirus in humans and dromedary camels in Diyala, Iraq.

Background: Middle East respiratory syndrome (MERS) is a zoonotic viral disease transmitted from dromedaries to humans. To date, more than 1500 cases of MERS have been reported and 80% of all cases have occurred in the Kingdom of Saudi Arabia (KSA). This cross-sectional study was carried out to figure out the rate of infection among humans and dromedary camels and to explore the risk factors.

Patterns of injury detected by pan-computed tomography after road traffic accidents: retrospective review from a trauma center in Saudi Arabia.

Background: Pan-scan (whole-body) computed tomography (CT) has a paramount role in the diagnosis of injuries in road traffic accidents (RTA).

Objective: Identify patterns of injuries on pan-CT scans.

Design: Retrospective medical record review.