IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 24, 2019
Detection and quantification of functional deficits due to moderate traumatic brain injury (mTBI) is crucial for clinical decision-making and timely commencement of functional therapy. In this work, we explore magnetoencephalography (MEG) based funct...
Research in developmental disabilities
Oct 24, 2019
BACKGROUND: Children with autism spectrum disorder (ASD) have deficits in their narrative skills and gestural communication. Very few intervention studies have been conducted with the aim of improving these skills.
Triple-negative breast cancer (TNBC), colon adenocarcinoma (COAD), ovarian cancer (OV), and glioblastoma multiforme (GBM) are common malignant tumors, in which significant challenges are still faced in early diagnosis, treatment, and prognosis. There...
Ovarian cancer (OC) is a common cause of cancer death among women worldwide, so there is a pressing need to identify factors influencing OC mortality. Much OC patient clinical data is publicly accessible via the Broad Institute Cancer Genome Atlas (T...
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...
Digitization of interstitial needles is a complicated and tedious process for the treatment planning of 3D CT image based interstitial high dose-rate brachytherapy (HDRBT) of gynecological cancer. We developed a deep-learning assisted auto-digitizati...
OBJECTIVE: Convolutional neural networks (CNNs) have proven successful as function approximators and have therefore been used for classification problems including electroencephalography (EEG) signal decoding for brain-computer interfaces (BCI). Arti...
Biological psychiatry. Cognitive neuroscience and neuroimaging
Oct 22, 2019
BACKGROUND: Theoretical models have emphasized systems-level abnormalities in major depressive disorder (MDD). For unbiased yet rigorous evaluations of pathophysiological mechanisms underlying MDD, it is critically important to develop data-driven ap...
BACKGROUND: We hypothesized utilizing machine learning (ML) algorithms for screening septic shock in ED would provide better accuracy than qSOFA or MEWS.
BACKGROUND: Substance use disorder (SUD) exacts enormous societal costs in the United States, and it is important to detect high-risk youths for prevention. Machine learning (ML) is the method to find patterns and make prediction from data. We hypoth...
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