Cardiovascular diseases (CVD) represent a significant global health challenge, often remaining undetected until severe cardiac events, such as heart attacks or strokes, occur. In regions like Qatar, research focused on non-invasive CVD identification...
PURPOSE: To develop a convolutional neural network (CNN) model to diagnose skull-base invasion by nasopharyngeal malignancies in CT images and evaluate the model's diagnostic performance.
PURPOSE: To evaluate the relationship between socioeconomic disadvantage using national area deprivation index (ADI) and CT-based body composition measures derived from fully automated artificial intelligence (AI) tools to identify body composition m...
OBJECTIVE: Since its introduction 25 years ago, the Invisalign® system has undergone multiple digital and biomechanical evolutions and its effectiveness is often compared to traditional systems without considering the many differences which character...
The emergence of collaborations, which standardize and combine multiple clinical databases across different regions, provide a wealthy source of data, which is fundamental for clinical prediction models, such as patient-level predictions. With the ai...
Robot assisted surgery (RAS) is increasingly used, and besides conventional minimally invasive surgery (cMIS) surgeons are challenged to learn an increased array of skills. This study aimed to assess the influence of both learning curves on each othe...
There is a lack of training curricula and educational concepts for robotic-assisted surgery (RAS). It remains unclear how surgical residents can be trained in this new technology and how robotics can be integrated into surgical residency training. Th...
Robot-assisted surgery is increasingly used in surgery for cancer. Reduced overview and loss of anatomical orientation are challenges that might be solved with image-guided surgical navigation using electromagnetic tracking (EMT). However, the robot'...
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