AIMC Topic: Reproducibility of Results

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A Study on the Application of Convolutional Neural Networks to Fall Detection Evaluated with Multiple Public Datasets.

Sensors (Basel, Switzerland)
Due to the repercussion of falls on both the health and self-sufficiency of older people and on the financial sustainability of healthcare systems, the study of wearable fall detection systems (FDSs) has gained much attention during the last years. T...

Recognition of Common Non-Normal Walking Actions Based on Relief-F Feature Selection and Relief-Bagging-SVM.

Sensors (Basel, Switzerland)
Action recognition algorithms are widely used in the fields of medical health and pedestrian dead reckoning (PDR). The classification and recognition of non-normal walking actions and normal walking actions are very important for improving the accura...

Deep learning-based target metabolite isolation and big data-driven measurement uncertainty estimation in proton magnetic resonance spectroscopy of the brain.

Magnetic resonance in medicine
PURPOSE: The aim of this study was to develop a method for metabolite quantification with simultaneous measurement uncertainty estimation in deep learning-based proton magnetic resonance spectroscopy ( H-MRS).

Biometric Identity Based on Intra-Body Communication Channel Characteristics and Machine Learning.

Sensors (Basel, Switzerland)
In this paper, we propose and validate using the Intra-body communications channel as a biometric identity. Combining experimental measurements collected from five subjects and two multi-layer tissue mimicking materials' phantoms, different machine l...

BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets.

Communications biology
Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortical landscape. Recent work established that macroscale brain organization and function can be describ...

Parametric generation of three-dimensional gait for robot-assisted rehabilitation.

Biology open
For robot-assisted rehabilitation and assessment of patients with motor dysfunction, the parametric generation of their normal gait as the input for the robot is essential to match with the features of the patient to a greater extent. In addition, th...

Comparing machine and human reviewers to evaluate the risk of bias in randomized controlled trials.

Research synthesis methods
BACKGROUND: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can...