ADHD/ADD

A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in ADHD.

The pathological mechanism of attention deficit hyperactivity disorder (ADHD) is incompletely specified, which leads to difficulty in precise diagnosis. Functional magnetic resonance imaging (fMRI) has emerged as a common neuroimaging technique for studying the brain functional connectome. Most existing methods that have either ignored or simply utilized graph structure, do not fully leverage the ...

Automatic detection of anteriorly displaced temporomandibular joint discs on magnetic resonance images using a deep learning algorithm.

OBJECTIVES: This study aimed to develop models that can automatically detect anterior disc displacement (ADD) of the temporomandibular joint (TMJ) on MRIs before orthodontic treatment to reduce the risk of developing serious complications after treatment.

Inter-Level Feature Balanced Fusion Network for Street Scene Segmentation.

Semantic segmentation, as a pixel-level recognition task, has been widely used in a variety of practical scenes. Most of the existing methods try to i...

Analyzing artificial intelligence systems for the prediction of atrial fibrillation from sinus-rhythm ECGs including demographics and feature visualization.

Atrial fibrillation (AF) is an abnormal heart rhythm, asymptomatic in many cases, that causes several health problems and mortality in population. Thi...

Predicting Success in the Embryology Lab: The Use of Algorithmic Technologies in Knowledge Production.

This article analyzes local algorithmic practices resulting from the increased use of time-lapse (TL) imaging in fertility treatment. The data produce...

TMJOAI: An Artificial Web-Based Intelligence Tool for Early Diagnosis of the Temporomandibular Joint Osteoarthritis.

Osteoarthritis is a chronic disease that affects the temporomandibular joint (TMJ), causing chronic pain and disability. To diagnose patients sufferin...

Prediction of corneal back surface power - Deep learning algorithm versus multivariate regression.

BACKGROUND: The corneal back surface is known to add some against the rule astigmatism, with implications in cataract surgery with toric lens implanta...

Combining genetic risk score with artificial neural network to predict the efficacy of folic acid therapy to hyperhomocysteinemia.

Artificial neural network (ANN) is the main tool to dig data and was inspired by the human brain and nervous system. Several studies clarified its app...

A Smart Capacitive Sensor Skin with Embedded Data Quality Indication for Enhanced Safety in Human-Robot Interaction.

Smart sensors are an integral part of the Fourth Industrial Revolution and are widely used to add safety measures to human-robot interaction applicati...

Human-Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human-Robot Collaboration.

Human-robot collaborative applications have been receiving increasing attention in industrial applications. The efficiency of the applications is ofte...

Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia.

Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain limited. The development of such tools can add va...

Automatic Film Label Acquisition Method Based on Improved Neural Networks Optimized by Mutation Ant Colony Algorithm.

Nowadays, with the constant change of public aesthetic standards, a large number of new types and themes of film programs have emerged. For this reaso...

Attention-Based Joint Training of Noise Suppression and Sound Event Detection for Noise-Robust Classification.

Sound event detection (SED) recognizes the corresponding sound event of an incoming signal and estimates its temporal boundary. Although SED has been ...

A novel deep learning model DDU-net using edge features to enhance brain tumor segmentation on MR images.

Glioma is a relatively common brain tumor disease with high mortality rate. Humans have been seeking a more effective therapy. In the course of treatm...

Research on Information Visualization Graphic Design Teaching Based on DBN Algorithm.

With the advent of the era of big data, how to quickly obtain effective information and efficiently disseminate information technology has become the ...

A Novel Handwritten Digit Classification System Based on Convolutional Neural Network Approach.

An enormous number of CNN classification algorithms have been proposed in the literature. Nevertheless, in these algorithms, appropriate filter size s...

Comparing Class-Aware and Pairwise Loss Functions for Deep Metric Learning in Wildlife Re-Identification.

Similarity learning using deep convolutional neural networks has been applied extensively in solving computer vision problems. This attraction is supp...

Deep neural network-estimated electrocardiographic age as a mortality predictor.

The electrocardiogram (ECG) is the most commonly used exam for the evaluation of cardiovascular diseases. Here we propose that the age predicted by ar...

Interpretable and explainable AI (XAI) model for spatial drought prediction.

Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a u...

Design of Deep Learning Model for Task-Evoked fMRI Data Classification.

Machine learning methods have been successfully applied to neuroimaging signals, one of which is to decode specific task states from functional magnet...