BACKGROUND AND AIMS: It is crucial to accurately determine malignant biliary strictures (MBSs) for early curative treatment. This study aimed to develop a real-time interpretable artificial intelligence (AI) system to predict MBSs under digital singl...
Risk prediction for heart failure (HF) using machine learning methods (MLM) has not yet been established at practical application levels in clinical settings. This study aimed to create a new risk prediction model for HF with a minimum number of pred...
PURPOSE: Magnetic resonance imaging (MRI) scan time remains a limited and valuable resource. This study evaluates the diagnostic performance of a deep learning (DL)-based accelerated TSE study protocol compared to a standard TSE study protocol in ank...
Artificial intelligence (AI), a branch of machine learning (ML) has been increasingly employed in the research of trauma in various aspects. Hemorrhage is the most common cause of trauma-related death. To better elucidate the current role of AI and c...
PURPOSE: This study aimed to compare motions of the laparoscope tip during a laparoscopic task in a training box using a recent joystick-guided robotic scope holder to those manipulated by human scopists. We hypothesized that laparoscopic manipulatio...
The global increase in antimicrobial drug resistance has dramatically reduced the effectiveness of traditional antibiotics. Structurally diverse antibiotics are urgently needed to combat multiple-resistant bacterial infections. As part of innate immu...
Deep learning (DL) is one of the most exciting new areas in medical imaging. This article will provide a review of current applications of DL in osteoarthritis (OA) imaging, including methods used for cartilage lesion detection, OA diagnosis, cartila...
We aimed to investigate the effects of video game habits, duration of experience, and training in different surgical clinics on the success of robotic surgery simulators. In this prospective, observational, comparative, and multi-clinical study, all ...
BACKGROUND : Deep learning models have previously been established to predict the histopathology and invasion depth of gastric lesions using endoscopic images. This study aimed to establish and validate a deep learning-based clinical decision support...
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Feb 6, 2023
PURPOSE: Postoperative complication prediction helps surgeons to inform and manage patient expectations. Deep learning, a model that finds patterns in large samples of data, outperform traditional statistical methods in making predictions. This study...
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