Studies regarding the influence of diabetes on perioperative outcomes after major hepatectomy are conflicting. The objective of this study is to analyze the effects of diabetes on patients undergoing robotic major hepatectomy. With Institutional Revi...
OBJECTIVES: This study aims to evaluate an automatic segmentation algorithm for pharyngeal airway in cone-beam computed tomography (CBCT) images using a deep learning artificial intelligence (AI) system.
BACKGROUND: Given the worldwide popularization of conventional minimally invasive esophagectomy (C-MIE), robot-assisted MIE (RAMIE) can be expected to provide a finer procedure. However, controversy remains regarding whether RAMIE is superior to C-MI...
PURPOSE: Robot-assisted laparoscopic prostatectomy (RALP) requires particular surgical conditions, such as carbon dioxide pneumoperitoneum and steep Trendelenburg positioning, which may have adverse effects on the respiratory system. The effect of su...
International journal of environmental research and public health
Mar 8, 2021
Assessment of risk before lung resection surgery can provide anesthesiologists with information about whether a patient can be weaned from the ventilator immediately after surgery. However, it is difficult for anesthesiologists to perform a complete ...
BACKGROUND: Machine learning is a useful tool for predicting medical outcomes. This study aimed to develop a machine learning-based preoperative score to predict cardiac surgical operative mortality.
OBJECTIVES: To evaluate the potential of a fully automatic artificial intelligence (AI)-driven computed tomography (CT) software prototype to quantify severity of COVID-19 infection on chest CT in relationship with clinical and laboratory data.
International journal of radiation oncology, biology, physics
Mar 6, 2021
PURPOSE: Our purpose was to develop a deep learning-based computed tomography (CT) perfusion mapping (DL-CTPM) method that synthesizes lung perfusion images from CT images.
RESEARCH QUESTION: Can artificial intelligence (AI) discriminate a blastocyst's cellular area from unedited time-lapse image files using semantic segmentation and a deep learning optimized U-Net architecture for use in selecting single blastocysts fo...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.