AIMC Topic: Young Adult

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Inpatient stroke rehabilitation: prediction of clinical outcomes using a machine-learning approach.

Journal of neuroengineering and rehabilitation
BACKGROUND: In clinical practice, therapists often rely on clinical outcome measures to quantify a patient's impairment and function. Predicting a patient's discharge outcome using baseline clinical information may help clinicians design more targete...

DeepNerve: A New Convolutional Neural Network for the Localization and Segmentation of the Median Nerve in Ultrasound Image Sequences.

Ultrasound in medicine & biology
Carpal tunnel syndrome commonly occurs in individuals working in occupations that involve use of vibrating manual tools or tasks with highly repetitive and forceful manual exertion. In recent years, carpal tunnel syndrome has been evaluated by ultras...

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...

Altered resting-state functional connectivity and effective connectivity of the habenula in irritable bowel syndrome: A cross-sectional and machine learning study.

Human brain mapping
Irritable bowel syndrome (IBS) is a disorder involving dysfunctional brain-gut interactions characterized by chronic recurrent abdominal pain, altered bowel habits, and negative emotion. Previous studies have linked the habenula to the pathophysiolog...

Effect of congenital adrenal hyperplasia treated by glucocorticoids on plasma metabolome: a machine-learning-based analysis.

Scientific reports
BACKGROUND: Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency leads to impaired cortisol biosynthesis. Treatment includes glucocorticoid supplementation. We studied the specific metabolomics signatures in CAH patients using two di...

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.

CAST: A multi-scale convolutional neural network based automated hippocampal subfield segmentation toolbox.

NeuroImage
In this study, we developed a multi-scale Convolutional neural network based Automated hippocampal subfield Segmentation Toolbox (CAST) for automated segmentation of hippocampal subfields. Although training CAST required approximately three days on a...