AIMC Topic: Adolescent

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Identifying psychosis spectrum youth using support vector machines and cerebral blood perfusion as measured by arterial spin labeled fMRI.

NeuroImage. Clinical
Altered cerebral blood flow (CBF), as measured by arterial spin labelling (ASL), has been observed in several psychiatric conditions, but is a generally underutilized MRI technique, especially in the study of psychosis spectrum (PS) symptoms. We aime...

Using machine learning to predict early readmission following esophagectomy.

The Journal of thoracic and cardiovascular surgery
OBJECTIVE: To establish a machine learning (ML)-based prediction model for readmission within 30 days (early readmission or early readmission) of patients based on their profile at index hospitalization for esophagectomy.

Automated computer-assisted detection system for cerebral aneurysms in time-of-flight magnetic resonance angiography using fully convolutional network.

Biomedical engineering online
BACKGROUND: As the rupture of cerebral aneurysm may lead to fatal results, early detection of unruptured aneurysms may save lives. At present, the contrast-unenhanced time-of-flight magnetic resonance angiography is one of the most commonly used meth...

S100 proteins, cytokines, and chemokines as tear biomarkers in children with juvenile idiopathic arthritis-associated uveitis.

Ocular immunology and inflammation
PURPOSE: Biomarkers for juvenile idiopathic arthritis-associated uveitis (JIA-U) are needed. We aimed to measure inflammatory biomarkers in tears as a non-invasive method to identify biomarkers of uveitis activity.

Classifying creativity: Applying machine learning techniques to divergent thinking EEG data.

NeuroImage
Prior research has shown that greater EEG alpha power (8-13 ​Hz) is characteristic of more creative individuals, and more creative task conditions. The present study investigated the potential for machine learning to classify more and less creative b...

Deep learning COVID-19 detection bias: accuracy through artificial intelligence.

International orthopaedics
BACKGROUND: Detection of COVID-19 cases' accuracy is posing a conundrum for scientists, physicians, and policy-makers. As of April 23, 2020, 2.7 million cases have been confirmed, over 190,000 people are dead, and about 750,000 people are reported re...

Pilot study: can machine learning analyses of movement discriminate between leg movements in sleep (LMS) with vs. without cortical arousals?

Sleep & breathing = Schlaf & Atmung
PURPOSE: Clinical and animal studies indicate frequent small micro-arousals (McA) fragment sleep leading to health complications. McA in humans is defined by changes in EEG and EMG during sleep. Complex EEG recordings during the night are usually req...

Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players.

Journal of science and medicine in sport
OBJECTIVES: The purpose of this study was to examine whether the use of machine learning improved the ability of a neuromuscular screen to identify injury risk factors in elite male youth football players.

Machine learning to quantify habitual physical activity in children with cerebral palsy.

Developmental medicine and child neurology
AIM: To investigate whether activity-monitors and machine learning models could provide accurate information about physical activity performed by children and adolescents with cerebral palsy (CP) who use mobility aids for ambulation.

Macroscale and microcircuit dissociation of focal and generalized human epilepsies.

Communications biology
Thalamo-cortical pathology plays key roles in both generalized and focal epilepsies, but there is little work directly comparing these syndromes at the level of whole-brain mechanisms. Using multimodal imaging, connectomics, and computational simulat...