AIMC Topic: Neural Networks, Computer

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Toward Concurrent Identification of Human Activities with a Single Unifying Neural Network Classification: First Step.

Sensors (Basel, Switzerland)
The characterization of human behavior in real-world contexts is critical for developing a comprehensive model of human health. Recent technological advancements have enabled wearables and sensors to passively and unobtrusively record and presumably ...

Artificial neural networks (ANN)-genetic algorithm (GA) optimization on thermosonicated achocha juice: kinetic and thermodynamic perspectives of retained phytocompounds.

Preparative biochemistry & biotechnology
The extraction of phytocompounds from Achocha () vegetable juice using traditional methods often results in suboptimal yields and efficiency. This study aimed to enhance the extraction process through the application of thermosonication (TS). To achi...

Motion Artifact Detection for T1-Weighted Brain MR Images Using Convolutional Neural Networks.

International journal of neural systems
Quality assessment (QA) of magnetic resonance imaging (MRI) encompasses several factors such as noise, contrast, homogeneity, and imaging artifacts. Quality evaluation is often not standardized and relies on the expertise, and vigilance of the person...

GateNet: A novel neural network architecture for automated flow cytometry gating.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Flow cytometry is a widely used technique for identifying cell populations in patient-derived fluids, such as peripheral blood (PB) or cerebrospinal fluid (CSF). Despite its ubiquity in research and clinical practice, the pr...

deepbet: Fast brain extraction of T1-weighted MRI using Convolutional Neural Networks.

Computers in biology and medicine
BACKGROUND: Brain extraction in magnetic resonance imaging (MRI) data is an important segmentation step in many neuroimaging preprocessing pipelines. Image segmentation is one of the research fields in which deep learning had the biggest impact in re...

Enhancing water quality monitoring through the integration of deep learning neural networks and fuzzy method.

Marine pollution bulletin
The escalating growth of the global population has led to degraded water quality, particularly in seawater environments. Water quality monitoring is crucial to understanding the dynamic changes and implementing effective management strategies. In thi...

The neural network RTNet exhibits the signatures of human perceptual decision-making.

Nature human behaviour
Convolutional neural networks show promise as models of biological vision. However, their decision behaviour, including the facts that they are deterministic and use equal numbers of computations for easy and difficult stimuli, differs markedly from ...

Smart Cushions with Machine Learning-Enhanced Force Sensors for Pressure Injury Risk Assessment.

ACS applied materials & interfaces
Prolonged sitting can easily result in pressure injury (PI) for certain people who have had strokes or spinal cord injuries. There are not many methods available for tracking contact surface pressure and shear force to evaluate the PI risk. Here, we ...

Explainable Deep-Learning-Based Gait Analysis of Hip-Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression.

Sensors (Basel, Switzerland)
Accurate prediction of scoliotic curve progression is crucial for guiding treatment decisions in adolescent idiopathic scoliosis (AIS). Traditional methods of assessing the likelihood of AIS progression are limited by variability and rely on static m...

Medical intelligence using PPG signals and hybrid learning at the edge to detect fatigue in physical activities.

Scientific reports
The educational environment plays a vital role in the development of students who participate in athletic pursuits both in terms of their physical health and their ability to detect fatigue. As a result of recent advancements in deep learning and bio...