OBJECTIVE: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction.
OBJECTIVE: To develop and validate a machine-learning algorithm to improve prediction of incident OUD diagnosis among Medicare beneficiaries with ≥1 opioid prescriptions.
OBJECTIVES: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus...
The international journal of cardiovascular imaging
Jul 16, 2020
To investigate the performance of a deep learning-based algorithm for fully automated quantification of left ventricular (LV) volumes and function in cardiac MRI. We retrospectively analysed MR examinations of 50 patients (74% men, median age 57 year...
OBJECTIVE: To determine whether training with a brain-computer interface (BCI) to control an image of a phantom hand, which moves based on cortical currents estimated from magnetoencephalographic signals, reduces phantom limb pain.
Predicting outcome in comatose patients after successful cardiopulmonary resuscitation is challenging. Our primary aim was to assess the potential contribution of resting-state-functional magnetic resonance imaging (RS-fMRI) in predicting neurologica...
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Jul 15, 2020
Clinical decision-making in kidney transplant (KT) during the coronavirus disease 2019 (COVID-19) pandemic is understandably a conundrum: both candidates and recipients may face increased acquisition risks and case fatality rates (CFRs). Given our po...
BACKGROUND: When pulmonary complications occur, postlobectomy patients have a higher mortality rate, increased length of stay, and higher readmission rates. Because of a lack of high-quality consolidated clinical data, it is challenging to assess and...
Balance impairment is critical for many patient groups such as those with neural and musculoskeletal disorders and also the elderly. Accurate and objective assessment of balance performance has led to the development of several indices based on the m...
BACKGROUND: Recently, artificial neural network (ANN) methods have also been adopted to deal with the complex multidimensional nonlinear relationship between clinicopathologic variables and survival for patients with gastric cancer. Using a multinati...
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