AIMC Topic: Machine Learning

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A Subject-Transfer Framework Based on Single-Trial EMG Analysis Using Convolutional Neural Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In recent years, electromyography (EMG)-based practical myoelectric interfaces have been developed to improve the quality of daily life for people with physical disabilities. With these interfaces, it is very important to decode a user's movement int...

A New Multimodel Machine Learning Framework to Improve Hepatic Fibrosis Grading Using Ultrasound Elastography Systems from Different Vendors.

Ultrasound in medicine & biology
The purpose of the work described here was to determine if the diagnostic performance of point and 2-D shear wave elastography (pSWE; 2-DSWE) using shear wave velocity (SWV) with a new machine learning (ML) technique applied to systems from different...

A machine-learning method for classifying and analyzing foot placement: Application to manual material handling.

Journal of biomechanics
Foot placement strategy is an essential aspect in the study of movement involving full body displacement. To get beyond a qualitative analysis, this paper provides a foot placement classification and analysis method that can be used in sports, rehabi...

Machine Learning-Assisted Array-Based Biomolecular Sensing Using Surface-Functionalized Carbon Dots.

ACS sensors
Fluorescent array-based sensing is an emerging differential sensing platform for sensitive detection of analytes in a complex environment without involving a conventional "lock and key" type-specific interaction. These sensing techniques mainly rely ...

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal.

Journal of visualized experiments : JoVE
Differential gene expression analysis is an important technique for understanding disease states. The machine learning algorithm CorEx has shown utility in analyzing differential expression of groups of genes in tumor RNA-seq in a way that may be hel...

An application of machine learning with feature selection to improve diagnosis and classification of neurodegenerative disorders.

BMC bioinformatics
BACKGROUND: The analysis of health and medical data is crucial for improving the diagnosis precision, treatments and prevention. In this field, machine learning techniques play a key role. However, the amount of health data acquired from digital mach...

Promoting head CT exams in the emergency department triage using a machine learning model.

Neuroradiology
PURPOSE: In this study, we aimed to develop a novel prediction model to identify patients in need of a non-contrast head CT exam during emergency department (ED) triage.

Joint optic disc and cup segmentation using semi-supervised conditional GANs.

Computers in biology and medicine
Glaucoma is a chronic and widespread eye disease threatening humans' irreversible vision loss. The cup-to-disc ratio (CDR), one of the most important measurements used for glaucoma screening and diagnosis, requires accurate segmentation of optic disc...

Estimating treatment effects with machine learning.

Health services research
OBJECTIVE: To demonstrate the performance of methodologies that include machine learning (ML) algorithms to estimate average treatment effects under the assumption of exogeneity (selection on observables).