AIMC Topic: Adult

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fNIRS-based Neurorobotic Interface for gait rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: In this paper, a novel functional near-infrared spectroscopy (fNIRS)-based brain-computer interface (BCI) framework for control of prosthetic legs and rehabilitation of patients suffering from locomotive disorders is presented.

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder.

Journal of psychiatric research
Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large variability is observed in terms of response to antidepressants. Machine learning (ML) models may be ...

Prediction of Occult Invasive Disease in Ductal Carcinoma in Situ Using Deep Learning Features.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to determine whether deep features extracted from digital mammograms using a pretrained deep convolutional neural network are prognostic of occult invasive disease for patients with ductal carcinoma in situ (DCIS) o...

Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables.

General hospital psychiatry
OBJECTIVE: To obtain predictors of suicidal ideation, which can also be used for an indirect assessment of suicidal ideation (SI). To create a classifier for SI based on variables of the Patient Health Questionnaire (PHQ) and sociodemographic variabl...

Interaction of Vitamin E Intake and Pro12Ala Polymorphism of PPARG with Adiponectin Levels.

Journal of nutrigenetics and nutrigenomics
BACKGROUND/AIM: One of the beneficial effects associated with vitamin E intake is the enhancement of peroxisome proliferator-activated receptor gamma (PPARγ) activity and the consequent upregulation of adiponectin expression. The aim of this study wa...

Using Convolutional Neural Networks for Enhanced Capture of Breast Parenchymal Complexity Patterns Associated with Breast Cancer Risk.

Academic radiology
RATIONALE AND OBJECTIVES: We evaluate utilizing convolutional neural networks (CNNs) to optimally fuse parenchymal complexity measurements generated by texture analysis into discriminative meta-features relevant for breast cancer risk prediction.

A Systematic Machine Learning Based Approach for the Diagnosis of Non-Alcoholic Fatty Liver Disease Risk and Progression.

Scientific reports
Prevention and diagnosis of NAFLD is an ongoing area of interest in the healthcare community. Screening is complicated by the fact that the accuracy of noninvasive testing lacks specificity and sensitivity to make and stage the diagnosis. Currently n...

Comparison of proximal versus distal upper-limb robotic rehabilitation on motor performance after stroke: a cluster controlled trial.

Scientific reports
This study examined the treatment efficacy of proximal-emphasized robotic rehabilitation by using the InMotion ARM (P-IMT) versus distal-emphasized robotic rehabilitation by using the InMotion WRIST (D-IMT) in patients with stroke. A total of 40 pati...

Detection of sleep disordered breathing severity using acoustic biomarker and machine learning techniques.

Biomedical engineering online
PURPOSE: Breathing sounds during sleep are altered and characterized by various acoustic specificities in patients with sleep disordered breathing (SDB). This study aimed to identify acoustic biomarkers indicative of the severity of SDB by analyzing ...

Lipid Metabolism in Patients with Anti-N-Methyl-D-Aspartate Receptor Encephalitis.

Neuroimmunomodulation
OBJECTIVE: Lipid metabolism has been implicated in autoimmune disorders, but its relationship with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is unclear. This study examined the association of serum lipids with anti-NMDAR encephalit...