INTRODUCTION: The purpose of the current study is to determine the accuracy of machine learning in predicting bleeding outcomes post percutaneous coronary intervention (PCI) in comparison with the American College of Cardiology CathPCI bleeding risk ...
BACKGROUND: Detection of atrial fibrillation (AF) occurrence over a long duration has been a challenge in the screening and follow-up of AF patients. Wearable devices may be an ideal solution.
BACKGROUND: Brain monitors tracking quantitative brain activities from electroencephalogram (EEG) to predict hypnotic levels have been proposed as a labor-saving alternative to behavioral assessments. Expensive clinical trials are required to validat...
BACKGROUND: Heart failure with reduced ejection fraction (HFrEF) is a condition imposing significant health care burden. Given its syndromic nature and often insidious onset, the diagnosis may not be made until clinical manifestations prompt further ...
BACKGROUND: Acute hypotensive episodes (AHE), defined as a drop in the mean arterial pressure (MAP) <65 mm Hg lasting at least 5 consecutive minutes, are among the most critical events in the intensive care unit (ICU). They are known to be associated...
BACKGROUND: Opioid-induced respiratory depression (OIRD) is traditionally recognized by assessment of respiratory rate, arterial oxygen saturation, end-tidal CO2, and mental status. Although an irregular or ataxic breathing pattern is widely recogniz...
OBJECTIVES: The objective of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for the fully automated per lobe segmentation and emphysema quantification (EQ) on chest-computed tomography as it compares to the Globa...
IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machi...
IMPORTANCE: The use of artificial intelligence (AI) is expanding throughout the field of medicine. In dermatology, researchers are evaluating the potential for direct-to-patient and clinician decision-support AI tools to classify skin lesions. Althou...
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