IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 29, 2019
Digitalized hand-drawn pattern is a noninvasive and reproducible assistive manner to obtain hand actions and motions for evaluating functional tremors and upper-limb movement disorders. In this study, spirals and straight lines in polar coordinates a...
BACKGROUND: Minimally invasive single-port surgery is often associated with large incisions up to 2-3 cm, complicated handling due to the lack of triangulation, and instrument crossing. Aim of this prospective study was to perform true single-port su...
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Oct 28, 2019
Machine learning (ML) applied to patient-reported (PROs) and clinical-assessed outcomes (CAOs) could favour a more predictive and personalized medicine. Our aim was to confirm the important role of applying ML to PROs and CAOs of people with relapsin...
BACKGROUND: - Adolescence is characterized by biological, emotional, and behavioral changes. The onset of depression during this vulnerable time may confer specific risks. This study examined whether symptoms of depression were associated with age at...
BACKGROUND: Liver alignment between series/exams is challenged by dynamic morphology or variability in patient positioning or motion. Image registration can improve image interpretation and lesion co-localization. We assessed the performance of a con...
Journal of neuroengineering and rehabilitation
Oct 26, 2019
BACKGROUND: The use of integrated robotic technology to quantify the spectrum of motor symptoms of Parkinson's Disease (PD) has the potential to facilitate objective assessment that is independent of clinical ratings. The purpose of this study is to ...
BACKGROUND: The ability to predict readmission accurately after hospitalization for acute myocardial infarction (AMI) is limited in current statistical models. Machine-learning (ML) methods have shown improved predictive ability in various clinical c...
BACKGROUND: Nonadherence to smoking cessation medication is a frequent problem. Identifying pre-quit predictors of nonadherence may help explain nonadherence and suggest tailored interventions to address it.
BACKGROUND: Machine learning (ML) is a powerful tool for identifying and structuring several informative variables for predictive tasks. Here, we investigated how ML algorithms may assist in echocardiographic pulmonary hypertension (PH) prediction, w...
Iranian journal of allergy, asthma, and immunology
Oct 23, 2019
The relationship between high levels of anti-Varicella Zoster Virus (VZV) IgG in cerebrospinal fluid (CSF) and cerebrovascular atherosclerosis commends a possible similar association in other vessels. We aimed to investigate the association of VZV-se...
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