Type 1 diabetes (T1D) is characterized by pancreatic beta cell dysfunction and insulin depletion. Over 40% of people with T1D manage their glucose through multiple injections of long-acting basal and short-acting bolus insulin, so-called multiple dai...
OBJECTIVES: This study investigated the impact of machine learning (ML)-based fractional flow reserve derived from computed tomography (FFR) compared to invasive coronary angiography (ICA) for therapeutic decision-making and patient outcome in patien...
RPL is a very debated condition, in which many issues concerning definition, etiological factors to investigate or therapies to apply are still controversial. ML could help clinicians to reach an objectiveness in RPL classification and access to care...
OBJECTIVE: To determine the potential impact of on-site CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD) on CCTA.
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the co...
Current neurology and neuroscience reports
Nov 13, 2019
PURPOSE OF REVIEW: Neurocritical care combines the complexity of both medical and surgical disease states with the inherent limitations of assessing patients with neurologic injury. Artificial intelligence (AI) has garnered interest in the basic mana...
Journal of clinical hypertension (Greenwich, Conn.)
Sep 19, 2019
Machine learning (ML) is a type of artificial intelligence (AI) based on pattern recognition. There are different forms of supervised and unsupervised learning algorithms that are being used to identify and predict blood pressure (BP) and other measu...
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