Latest AI and machine learning research in emergency medicine for healthcare professionals.
Acute kidney injury (AKI) after percutaneous coronary intervention (PCI) is associated with a signif...
OBJECTIVES: This study intends to build and compare two kinds of forecasting models at different tim...
BACKGROUND: Social robots (SRs) have been used for improving anxiety in children in stressful clinic...
BACKGROUND: There are often many missing values in medical data, which directly affect the accuracy ...
Endometriosis-a systemic and chronic condition occurring in women of childbearing age-is a highly en...
This paper reported a study on the 3-dimensional deep-learning-based automatic diagnosis of nasal fr...
BACKGROUND: For the robot-assisted fracture reduction, due to the complex fracture musculoskeletal e...
The first ever insurance reimbursement for an artificial intelligence (AI) system, which expedites t...
PURPOSE: To compare the image quality between a deep learning-based image reconstruction algorithm (...
Emamectin benzoate (EMB) is a potent neurotoxin agent, widely used for ectoparasites control in aqua...
Drug-resistant superbugs (DRS) were isolated from hospital sewage waste and confirmed by a 16S rDNA ...
BACKGROUND: Detection and quantification of intra-abdominal free fluid (ie, ascites) on computed tom...
A 76-year-old lady was found on the floor following a fall at home. She was uninjured, but unable to...
We derived machine learning models utilizing features generated by natural language processing (NLP)...
Big data (BD) and artificial intelligence (AI) have increasingly been used in neurocritical care. "B...
BACKGROUND: Emergency department (ED) crowding has resulted in delayed patient treatment and has bec...
In the last two decades, cochlear implant surgery has evolved into a minimally invasive, hearing pre...
PURPOSE: Ventilator-associated pneumonia is the most common nosocomial infection in patients with me...
The application of artificial intelligence (AI) technology in the medical field has experienced a lo...
Background Missed fractures are a common cause of diagnostic discrepancy between initial radiographi...
In recent years, fracture image diagnosis using a convolutional neural network (CNN) has been report...