The reproductive management of mares for frozen semen artificial insemination (AI) can be costly and labor intensive. Predicting the exact time of ovulation can be challenging even when ovulation-inducing drugs are used. The main objective of this re...
BACKGROUND: Motor impairment and loss of ambulatory function are major consequences of a spinal cord injury (SCI). Exoskeletons are robotic devices that allow SCI patients with limited ambulatory function to walk. The mean walking speed of SCI patien...
Recent studies have reported the application of artificial neural network (ANN) techniques on data of inertial measurement units (IMUs) to predict ground reaction forces (GRFs), which could serve as quantitative indicators of sports performance or re...
European child & adolescent psychiatry
Dec 23, 2019
To improve the prediction of the individual risk of conversion to psychosis in UHR subjects, by considering all CAARMS' symptoms at first presentation and using a multivariate machine learning method known as logistic regression with Elastic-net shri...
BACKGROUND/AIMS: To compare intraocular pressure (IOP) measurements using a prototype smartphone tonometer with other tonometers used in clinical practice.
Journal of neurointerventional surgery
Dec 23, 2019
BACKGROUND AND PURPOSE: Infarct volume is a valuable outcome measure in treatment trials of acute ischemic stroke and is strongly associated with functional outcome. Its manual volumetric assessment is, however, too demanding to be implemented in cli...
PURPOSE: To validate the efficacy of a fully automatic, deep learning-based segmentation algorithm beyond conventional performance metrics by measuring the primary outcome of a clinical trial for macular telangiectasia type 2 (MacTel2).
BACKGROUND: Low cardiorespiratory fitness is an independent predictor of all-cause and cardiovascular mortality, and interventions that increase fitness reduce risk. Water-walking decreases musculoskeletal impact and risk of falls in older individual...
Development of label-free methods for accurate classification of cells with high throughput can yield powerful tools for biological research and clinical applications. We have developed a deep neural network of DINet for extracting features from cros...
BACKGROUND AND AIMS: Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary compute...
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