The medical literature has been growing exponentially, and its size has become a barrier for physicians to locate and extract clinically useful information. As a promising solution, natural language processing (NLP), especially machine learning (ML)-...
Computer assisted automatic smart pattern analysis of cancer affected pixel structure takes critical role in pre-interventional decision making for oral cancer treatment. Internet of Things (IoT) in healthcare systems is now emerging solution for mod...
BACKGROUND: Antibiotic exposure is often inadequate in critically ill patients with severe sepsis or septic shock and this is associated with worse outcomes. Despite markedly altered and rapidly changing pharmacokinetics in these patients, guidelines...
BACKGROUND: In the hospital setting, it is crucial to identify patients at risk for deterioration before it fully develops, so providers can respond rapidly to reverse the deterioration. Rapid response (RR) activation criteria include a subjective co...
The analysis of trace hydrophilic targets in complex aqueous-rich matrices is considerably challenging, generally requiring matrix-matched calibration, internal standard, or time-and-labor-intensive sample preparation. To address this analytical bott...
PURPOSE: To assess the performance of machine learning classifiers for prediction of progression of normal-tension glaucoma (NTG) in young myopic patients.
Brain tumor detection depicts a tough job because of its shape, size and appearance variations. In this manuscript, a deep learning model is deployed to predict input slices as a tumor (unhealthy)/non-tumor (healthy). This manuscript employs a high p...
BMC medical informatics and decision making
Dec 17, 2019
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that is classified into stages based on disease severity. We aimed to characterize the time to progression prior to death in patients with COPD and to generate a t...
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