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Reproducibility of importance extraction methods in neural network based fMRI classification.

NeuroImage
Recent advances in machine learning allow faster training, improved performance and increased interpretability of classification techniques. Consequently, their application in neuroscience is rapidly increasing. While classification approaches have p...

When robots care: Public deliberations on how technology and humans may support independent living for older adults.

Social science & medicine (1982)
While assistive robots receive growing attention as a potential solution to support older adults to live independently, several scholars question the underlying social, ethical and health policy assumptions. One perplexing issue is determining whethe...

Assessment of Carotid Artery Plaque Components With Machine Learning Classification Using Homodyned-K Parametric Maps and Elastograms.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide compl...

Cuff Pressure Algometry in Patients with Chronic Pain as Guidance for Circumferential Tissue Compression for Wearable Soft Exoskeletons: A Systematic Review.

Soft robotics
In this article, we report on a systematic review of the literature on pressure-pain thresholds induced and assessed by computerized cuff pressure algometry (CPA). The motivation for this review is to provide design guidance on pressure levels for we...

Gait Estimation from Anatomical Foot Parameters Measured by a Foot Feature Measurement System using a Deep Neural Network Model.

Scientific reports
An accurate and credible measurement of human gait is essential in multiple areas of medical science and rehabilitation. Yet, the methods currently available are not only arduous but also costly. Researchers who investigated the relationship between ...

Bioimpedance and New-Onset Heart Failure: A Longitudinal Study of >500 000 Individuals From the General Population.

Journal of the American Heart Association
BACKGROUND: Heart failure constitutes a high burden on patients and society, but although lifetime risk is high, it is difficult to predict without costly or invasive testing. We aimed to establish new risk factors of heart failure, which potentially...

Introducing chaos behavior to kernel relevance vector machine (RVM) for four-class EEG classification.

PloS one
This paper addresses a chaos kernel function for the relevance vector machine (RVM) in EEG signal classification, which is an important component of Brain-Computer Interface (BCI). The novel kernel function has evolved from a chaotic system, which is...

Detecting intertrochanteric hip fractures with orthopedist-level accuracy using a deep convolutional neural network.

Skeletal radiology
OBJECTIVE: To compare performances in diagnosing intertrochanteric hip fractures from proximal femoral radiographs between a convolutional neural network and orthopedic surgeons.

Machine learning models to predict the progression from early to late stages of papillary renal cell carcinoma.

Computers in biology and medicine
Papillary Renal Cell Carcinoma (PRCC) is a heterogeneous disease with variations in disease progression and clinical outcomes. The advent of next generation sequencing techniques (NGS) has generated data from patients that can be analysed to develop ...