The diagnosis and prognosis of traumatic brain injury (TBI) is complicated by variability in the type and severity of injuries and the multiple endophenotypes that describe each patient's response and recovery to the injury. It has been challenging t...
The study examines employability attributes as psychological mechanisms that explain the link between the career adaptation concerns and self-perceived employability of a sample of professionally qualified knowledge workers (N = 404). A cross-section...
Asia-Pacific journal of clinical oncology
May 6, 2019
AIM: To describe national surgical patterns of prostate cancer (PCa) care considering radical prostatectomy with or without pelvic lymphadenectomy and consideration of robotic-assisted techniques.
PURPOSE: The purpose of this study was to assess the perception, knowledge, wishes and expectations of a sample of French radiologists towards the rise of artificial intelligence (AI) in radiology.
The Cox proportional hazards model commonly used to evaluate prognostic variables in survival of cancer patients may be too simplistic to properly predict a cancer patient's outcome since it assumes that the outcome is a linear combination of covaria...
OBJECTIVE: To compare axonal loss in ganglion cells detected with swept-source optical coherence tomography (SS-OCT) in eyes of patients with multiple sclerosis (MS) versus healthy controls using different machine learning techniques. To analyze the ...
The spine journal : official journal of the North American Spine Society
May 4, 2019
BACKGROUND CONTEXT: Data regarding risk of failure of nonoperative management in spinal epidural abscess (SEA) are limited. Given the potential for deterioration with treatment failure, a tool that predicts the probability of failure would be of grea...
BACKGROUND AND AIMS: Although grayscale intravascular ultrasound (IVUS) is commonly used for assessing coronary lesion morphology and optimizing stent implantation, detection of vulnerable plaques by IVUS remains challenging. We aimed to develop mach...
We introduce two Convolutional Neural Network (CNN) classifiers optimized for inferring brain states from magnetoencephalographic (MEG) measurements. Network design follows a generative model of the electromagnetic (EEG and MEG) brain signals allowin...
Risk stratification of patients with gastrointestinal bleeding (GIB) is recommended, but current risk assessment tools have variable performance. Machine learning (ML) has promise to improve risk assessment. We performed a systematic review to evalua...
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