ADHD/ADD

Ensemble classification combining ResNet and handcrafted features with three-steps training.

This work presents an ECG classifier for variable leads as a contribution to the Computing in Cardiology Challenge/CinC Challenge 2021. It aims to integrate deep and classic machine learning features into a single model, exploring the proper structure and training procedure.From the initial 88 253 signals, only 84 210 were included. Low quality and unscored recordings were excluded. Three differen...

Toward Mental Effort Measurement Using Electrodermal Activity Features.

The ability to monitor mental effort during a task using a wearable sensor may improve productivity for both work and study. The use of the electrodermal activity (EDA) signal for tracking mental effort is an emerging area of research. Through analysis of over 92 h of data collected with the Empatica E4 on a single participant across 91 different activities, we report on the efficacy of using EDA ...

Computational Modeling of Structural Synaptic Plasticity in Echo State Networks.

Most existing studies on computational modeling of neural plasticity have focused on synaptic plasticity. However, regulation of the internal weights ...

Learning From Synthetic CT Images via Test-Time Training for Liver Tumor Segmentation.

Automatic liver tumor segmentation could offer assistance to radiologists in liver tumor diagnosis, and its performance has been significantly improve...

Accurate image-based identification of macroinvertebrate specimens using deep learning-How much training data is needed?

Image-based methods for species identification offer cost-efficient solutions for biomonitoring. This is particularly relevant for invertebrate studie...

A Neural Network Model for Color Element Data Analysis for Urban Spatial Environment.

In this paper, a CNN model for color element data analysis of the urban spatial environment is constructed through an in-depth study of color element ...

Biomedical Relation Extraction With Knowledge Graph-Based Recommendations.

Biomedical Relation Extraction (RE) systems identify and classify relations between biomedical entities to enhance our knowledge of biological and med...

A privacy preservation framework for feedforward-designed convolutional neural networks.

A feedforward-designed convolutional neural network (FF-CNN) is an interpretable neural network with low training complexity. Unlike a neural network ...

Decision-Making Application of the Cloud-Fog Hybrid Model Based on the Improved Convolutional Neural Network in Financial Services in Smart Medical Care.

In order to alleviate the "difficulty in seeing a doctor" for the masses, continuously optimize the service process, and explore new financial service...

Value-free random exploration is linked to impulsivity.

Deciding whether to forgo a good choice in favour of exploring a potentially more rewarding alternative is one of the most challenging arbitrations bo...

Novel Coronavirus and Common Pneumonia Detection from CT Scans Using Deep Learning-Based Extracted Features.

COVID-19 which was announced as a pandemic on 11 March 2020, is still infecting millions to date as the vaccines that have been developed do not preve...

Ultrasound enhanced butyric acid-lauric acid designer lipid synthesis: Based on artificial neural network and changes in enzymatic structure.

Ultrasound is a green technology for intensifying enzymatic reactions. In this study, an ultrasonic water bath with equipment parameters of 28 kHz, 17...

A Lightweight Subgraph-Based Deep Learning Approach for Fall Recognition.

Falls pose a great danger to social development, especially to the elderly population. When a fall occurs, the body's center of gravity moves from a h...

Adaptive Modular Convolutional Neural Network for Image Recognition.

Image recognition has long been one of the research hotspots in computer vision tasks. The development of deep learning is rapid in recent years, and ...

Facility Layout Optimization of Urban Public Sports Services under the Background of Deep Learning.

The spatial layout and optimization of social facilities for sports are related to many factors such as urban economy, transportation, population, and...

TSTELM: Two-Stage Transfer Extreme Learning Machine for Unsupervised Domain Adaptation.

As a single-layer feedforward network (SLFN), extreme learning machine (ELM) has been successfully applied for classification and regression in machin...

Deep learning with multiresolution handcrafted features for brain MRI segmentation.

The segmentation of magnetic resonance (MR) images is a crucial task for creating pseudo computed tomography (CT) images which are used to achieve pos...

A Novel Deep Learning and Ensemble Learning Mechanism for Delta-Type COVID-19 Detection.

Recently, the novel coronavirus disease 2019 (COVID-19) has posed many challenges to the research community by presenting grievous severe acute respir...

Recurrent neural network based high-precision position compensation control of magnetic levitation system.

For improving the dynamic quality and steady-state performance, the hybrid controller based on recurrent neural network (RNN) is designed to implement...

Advantages of deep learning with convolutional neural network in detecting disc displacement of the temporomandibular joint in magnetic resonance imaging.

This study investigated the usefulness of deep learning-based automatic detection of anterior disc displacement (ADD) from magnetic resonance imaging ...