AIMC Topic: Middle Aged

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Application of machine learning to determine top predictors of noncalcified coronary burden in psoriasis: An observational cohort study.

Journal of the American Academy of Dermatology
BACKGROUND: Psoriasis is associated with elevated risk of heart attack and increased accumulation of subclinical noncalcified coronary burden by coronary computed tomography angiography (CCTA). Machine learning algorithms have been shown to effective...

Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders.

Computers in biology and medicine
BACKGROUND: Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progressively impairs cognitive functions. Computer-assisted diagnosis of AD based on image analysis is an emerging tool to support AD diagnosis. In this arti...

Comparison of Bagging and Boosting Ensemble Machine Learning Methods for Automated EMG Signal Classification.

BioMed research international
The neuromuscular disorders are diagnosed using electromyographic (EMG) signals. Machine learning algorithms are employed as a decision support system to diagnose neuromuscular disorders. This paper compares bagging and boosting ensemble learning met...

A neural network-based algorithm for predicting the spontaneous passage of ureteral stones.

Urolithiasis
In this study, a prototype artificial neural network model (ANN) was used to estimate the stone passage rate and to determine the effectivity of predictive factors on this rate in patients with ureteral stones. The retrospective study included a tota...

Clinical non-superiority of technology-assisted gait training with body weight support in patients with subacute stroke: A meta-analysis.

Annals of physical and rehabilitation medicine
BACKGROUND: Technology-assisted gait training (TAGT) with body weight support (BWS) has been designed to provide high numbers of repetitions during stepping practice, but its benefits have been inconclusive.

Machine learning-based prediction of radiographic progression in patients with axial spondyloarthritis.

Clinical rheumatology
INTRODUCTION: Machine learning is applied to characterize the risk and predict outcomes in multi-dimensional data. The prediction of radiographic progression in axial spondyloarthritis (axSpA) remains limited. Hence, we tested the feasibility of supe...

Robot-assisted Nipple-sparing Mastectomy with Immediate Breast Reconstruction: An Initial Experience.

Scientific reports
Seeking smaller and indistinct incisions, physicians have attempted endoscopic breast surgery in breast cancer patients. Unfortunately, there are some limitations in the range of movement and visualization of the operation field. Potentially addressi...

Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks.

Nature communications
The discovery that deep convolutional neural networks (DCNNs) achieve human performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties to such tasks. Here we show that the face-space geometry, revealed through pa...

Machine learning techniques to predict the effectiveness of music therapy: A randomized controlled trial.

Computer methods and programs in biomedicine
BACKGROUND: The literature shows the effectiveness of music listening, but which factors and what types of music produce therapeutic effects, as well as how music therapists can select music, remain unclear. Here, we present a study to establish the ...