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Noninvasive Total Cholesterol Level Measurement Using an E-Nose System and Machine Learning on Exhaled Breath Samples.

ACS sensors
In this paper, the first e-nose system coupled with machine learning algorithm for noninvasive measurement of total cholesterol level based on exhaled air sample was proposed. The study was conducted with the participation of 151 people, from whom a ...

Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding.

Journal of translational medicine
BACKGROUND: The global outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damaging, in which prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously 2019-nCoV) infection is a challenge in the...

Using Machine Learning to Predict the Duration of Atrial Fibrillation: Model Development and Validation.

JMIR medical informatics
BACKGROUND: Atrial fibrillation (AF) is a progressive disease, and its clinical type is classified according to the AF duration: paroxysmal AF, persistent AF (PeAF; AF duration of less than 1 year), and long-standing persistent AF (AF duration of mor...

Reproducing the caress gesture with an anthropomorphic robot: a feasibility study.

Bioinspiration & biomimetics
Social robots have been widely used to deliver emotional, cognitive and social support to humans. The exchange of affective gestures, instead, has been explored to a lesser extent, despite phyisical interaction with social robots could provide the sa...

The use of machine learning to understand the role of visual attention in multi-attribute choice.

Acta psychologica
Whether eye movements (as a measure of visual attention) contribute to the understanding of how multi-attribute decisions are made, is still a matter of debate. In this study, we show how machine learning methods can be used to separate the effects o...

Classifying age from medial clavicle using a 30-year threshold: An image analysis based approach.

PloS one
This study aimed to develop image-analysis-based classification models for distinguishing individuals younger and older than 30 using the medial clavicle. We extracted 2D images of the medial clavicle from multi-slice computed tomography (MSCT) scans...

Evolution of Linguistic Markers of Agency, Centrality and Content During Metacognitive Therapy for Psychosis: A Pilot Exploratory Study.

Early intervention in psychiatry
AIM: Metacognitive Reflection and Insight Therapy (MERIT) is a form of person-centred psychotherapy that promotes recovery-oriented outcomes by targeting metacognitive capacity. Previous research has shown the feasibility and clinical benefits of MER...

Learning a Hand Model From Dynamic Movements Using High-Density EMG and Convolutional Neural Networks.

IEEE transactions on bio-medical engineering
OBJECTIVE: Surface electromyography (sEMG) can sense the motor commands transmitted to the muscles. This work presents a deep learning method that can decode the electrophysiological activity of the forearm muscles into the movements of the human han...

A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development.

IEEE transactions on bio-medical engineering
OBJECTIVE: Brain dynamic effective connectivity (dEC), characterizes the information transmission patterns between brain regions that change over time, which provides insight into the biological mechanism underlying brain development. However, most e...