BACKGROUND: Scedosporiasis is an emerging mycosis that has gained importance in recent years due to its worldwide prevalence. It is caused by species of the Scedosporium apiospermum complex. These species can cause opportunistic infections in immunoc...
For designing the assistive wearable rehabilitation robots, it is challenging to design the robot as energy efficient because the actuators have to be capable of overcoming human loads such as gravity of the body and spastic torque continuously durin...
Artificial intelligence revolutionizes nursing informatics and healthcare by enhancing patient outcomes and healthcare access while streamlining nursing workflow. These advancements, while promising, have sparked debates on traditional nursing ethics...
OBJECTIVE: To investigate the accuracy of artificial intelligence-assisted growth prediction using a convolutional neural network (CNN) algorithm and longitudinal lateral cephalograms (Lat-cephs).
Journal of imaging informatics in medicine
Feb 6, 2024
This study aimed to examine the feasibility of utilizing radiomics models derived from F-FDG PET/CT imaging to screen for T-cell lymphoma in children with lymphoma. All patients had undergone F-FDG PET/CT scans. Lesions were extracted from PET/CT and...
Oral surgery, oral medicine, oral pathology and oral radiology
Feb 6, 2024
OBJECTIVES: In this study, we assessed 6 different artificial intelligence (AI) chatbots (Bing, GPT-3.5, GPT-4, Google Bard, Claude, Sage) responses to controversial and difficult questions in oral pathology, oral medicine, and oral radiology.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 6, 2024
Automated medical image segmentation plays a crucial role in diverse clinical applications. The high annotation costs of fully-supervised medical segmentation methods have spurred a growing interest in semi-supervised methods. Existing semi-supervise...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 6, 2024
Low resolution of positron emission tomography (PET) limits its diagnostic performance. Deep learning has been successfully applied to achieve super-resolution PET. However, commonly used supervised learning methods in this context require many pairs...
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