BACKGROUND: Many mortality prediction models have been developed for patients in intensive care units (ICUs); most are based on data available at ICU admission. We investigated whether machine learning methods using analyses of time-series data impro...
International journal of environmental research and public health
Mar 12, 2020
Timely stroke diagnosis and intervention are necessary considering its high prevalence. Previous studies have mainly focused on stroke prediction with balanced data. Thus, this study aimed to develop machine learning models for predicting stroke with...
BACKGROUND: MRI scanning has revolutionized the clinical diagnosis of lumbar spinal stenosis (LSS). However, there is currently no consensus as to how best to classify MRI findings which has hampered the development of robust longitudinal epidemiolog...
Pseudoaneurysm occurs when the artery wall is damaged and the blood is contained by the surrounding tissues with the eventual formation of a fibrous sac communicating with the artery. We report a case of a 74-year-old man with inferior epigastric art...
OBJECTIVES: Pneumothorax is the most common and potentially life-threatening complication arising from percutaneous lung biopsy. We evaluated the performance of a deep learning algorithm for detection of post-biopsy pneumothorax in chest radiographs ...
OBJECTIVE: Clinical trials in amyotrophic lateral sclerosis (ALS) continue to rely on survival or functional scales as endpoints, despite the emergence of quantitative biomarkers. Neuroimaging-based biomarkers in ALS have been shown to detect ALS-ass...
Computational intelligence and neuroscience
Mar 11, 2020
Traumatic brain injury (TBI) is one of the injuries that can bring serious consequences if medical attention has been delayed. Commonly, analysis of computed tomography (CT) or magnetic resonance imaging (MRI) is required to determine the severity of...
The American journal of emergency medicine
Mar 10, 2020
BACKGROUND: Low-acuity outpatients constitute the majority of emergency department (ED) patients, and these patients often experience an unpredictable length of stay (LOS). Effective LOS prediction might improve the quality of ED care and reduce ED c...
Robot-assisted rehabilitation is an appealing strategy for patients after stroke, as it generates repetitive movements in a consistent, precise, and automated manner. To identify patients who will benefit most from robotic rehabilitation for upper ...
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