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Use of a convolutional neural network for the classification of microbeads in urban wastewater.

Chemosphere
Scientists are on the lookout for a practical model that can serve as a standard for sorting out, identifying, and characterizing microplastics which are common occurrences in water sources and wastewaters. The microbeads (MBs) used in cosmetics and ...

Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling.

Computers in biology and medicine
We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibrillation, are a major global healthcare challenge. Treatment is often th...

The future is coming: promising perspectives regarding the use of machine learning in renal transplantation.

Jornal brasileiro de nefrologia
INTRODUCTION: The prediction of post transplantation outcomes is clinically important and involves several problems. The current prediction models based on standard statistics are very complex, difficult to validate and do not provide accurate predic...

Social-cue perception and mentalizing ability following traumatic brain injury: A human-robot interaction study.

Brain injury
PRIMARY OBJECTIVE: Research studies and clinical observations of individuals with traumatic brain injury (TBI) indicate marked deficits in mentalizing-perceiving social information and integrating it into judgements about the affective and mental sta...

SCREEN-DR: Collaborative platform for diabetic retinopathy.

International journal of medical informatics
BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR) is the most prevalent microvascular complication of diabetes mellitus and can lead to irreversible visual loss. Screening programs, based on retinal imaging techniques, are fundamental to detect the...

Regulation of C2C12 Differentiation and Control of the Beating Dynamics of Contractile Cells for a Muscle-Driven Biosyncretic Crawler by Electrical Stimulation.

Soft robotics
Biosyncretic robots have potential advantages associated with both living organisms and electromechanical systems. Skeletal muscle tissue is a candidate as bioactuators for biosyncretic robots because of its excellent contraction force and controllab...

Machine Meets Biology: a Primer on Artificial Intelligence in Cardiology and Cardiac Imaging.

Current cardiology reports
PURPOSE OF REVIEW: An understanding of the basics concepts of deep learning can be helpful in not only understanding the potential applications of this technique but also in critically reviewing literature in which neural networks are utilized for an...

ECG Signal Classification Using Various Machine Learning Techniques.

Journal of medical systems
Electrocardiogram (ECG) signal is a process that records the heart rate by using electrodes and detects small electrical changes for each heat rate. It is used to investigate some types of abnormal heart function including arrhythmias and conduction ...