BACKGROUND: The US population is becoming more racially and ethnically diverse. Research suggests that cultural diversity within organizations can increase team potency and performance, yet this theory has not been explored in the field of surgery. F...
AIMS: Machine learning (ML) is widely believed to be able to learn complex hidden interactions from the data and has the potential in predicting events such as heart failure (HF) readmission and death. Recent studies have revealed conflicting results...
OBJECTIVES: This study sought to develop a fully automated framework for cardiac function analysis from cardiac magnetic resonance (CMR), including comprehensive quality control (QC) algorithms to detect erroneous output.
BACKGROUND: We examined whether a context and process-sensitive 'intelligent' checklist increases compliance with best practice compared with a paper checklist during intensive care ward rounds.
BACKGROUND: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect to the implementation of artificial intelligence (AI) and deep learning in pathology, including cyt...
In order to explore the quality management efficiency of applying big data and artificial intelligence in nursing quality index, a method of building a nursing management platform integrating nursing indicators and nursing events is proposed. Based o...
Clinical and translational gastroenterology
34128480
INTRODUCTION: Gastrointestinal endoscopic quality is operator-dependent. To ensure the endoscopy quality, we constructed an endoscopic audit and feedback system named Endo.Adm and evaluated its effect in a form of pretest and posttest trial.