AIMC Topic: Smartphone

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Early detection of visual impairment in young children using a smartphone-based deep learning system.

Nature medicine
Early detection of visual impairment is crucial but is frequently missed in young children, who are capable of only limited cooperation with standard vision tests. Although certain features of visually impaired children, such as facial appearance and...

Smartphones dependency risk analysis using machine-learning predictive models.

Scientific reports
Recent technological advances have changed how people interact, run businesses, learn, and use their free time. The advantages and facilities provided by electronic devices have played a major role. On the other hand, extensive use of such technology...

A Smartphone-Based Platform Assisted by Artificial Intelligence for Reading and Reporting Rapid Diagnostic Tests: Evaluation Study in SARS-CoV-2 Lateral Flow Immunoassays.

JMIR public health and surveillance
BACKGROUND: Rapid diagnostic tests (RDTs) are being widely used to manage COVID-19 pandemic. However, many results remain unreported or unconfirmed, altering a correct epidemiological surveillance.

Ensemble of RNN Classifiers for Activity Detection Using a Smartphone and Supporting Nodes.

Sensors (Basel, Switzerland)
Nowadays, sensor-equipped mobile devices allow us to detect basic daily activities accurately. However, the accuracy of the existing activity recognition methods decreases rapidly if the set of activities is extended and includes training routines, s...

Path Generator with Unpaired Samples Employing Generative Adversarial Networks.

Sensors (Basel, Switzerland)
Interactive technologies such as augmented reality have grown in popularity, but specialized sensors and high computer power must be used to perceive and analyze the environment in order to obtain an immersive experience in real time. However, these ...

Portable, Automated and Deep-Learning-Enabled Microscopy for Smartphone-Tethered Optical Platform Towards Remote Homecare Diagnostics: A Review.

Small methods
Globally new pandemic diseases induce urgent demands for portable diagnostic systems to prevent and control infectious diseases. Smartphone-based portable diagnostic devices are significantly efficient tools to user-friendly connect personalized heal...

Matched Filter Interpretation of CNN Classifiers with Application to HAR.

Sensors (Basel, Switzerland)
Time series classification is an active research topic due to its wide range of applications and the proliferation of sensory data. Convolutional neural networks (CNNs) are ubiquitous in modern machine learning (ML) models. In this work, we present a...

A Systematic Review of Time Series Classification Techniques Used in Biomedical Applications.

Sensors (Basel, Switzerland)
Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, and ingestible and implantable sensors are increasingly used by individuals and clinicians to capture the health outcomes or b...

HIT HAR: Human Image Threshing Machine for Human Activity Recognition Using Deep Learning Models.

Computational intelligence and neuroscience
In recent days, research in human activity recognition (HAR) has played a significant role in healthcare systems. The accurate activity classification results from the HAR enhance the performance of the healthcare system with broad applications. HAR ...