Autism

Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment.

Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolution, has been used in many frontiers, including education, security, gaming, finance, robotics, autonomous systems, entertainment, and most importantly ...

Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes.

Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated wit...

Predicting Genetic Disorder and Types of Disorder Using Chain Classifier Approach.

Genetic disorders are the result of mutation in the deoxyribonucleic acid (DNA) sequence which can be developed or inherited from parents. Such mutati...

Big data and artificial intelligence application in energy field: a bibliometric analysis.

This paper uses bibliometrics to characterize the knowledge systems of big data, artificial intelligence (AI), and energy based on the Science Citatio...

Computer-aided diagnosis of autism spectrum disorder from EEG signals using deep learning with FAWT and multiscale permutation entropy features.

Autism spectrum disorder (ASD), a neurodevelopment disorder, is characterized by significant difficulties in social interaction and emerges as a major...

Predicting Antigenic Distance from Genetic Data for PRRSV-Type 1: Applications of Machine Learning.

The control of porcine reproductive and respiratory syndrome (PRRS) remains a significant challenge due to the genetic and antigenic variability of th...

Scratch-AID, a deep learning-based system for automatic detection of mouse scratching behavior with high accuracy.

Mice are the most commonly used model animals for itch research and for development of anti-itch drugs. Most laboratories manually quantify mouse scra...

Artificial intelligence model with deep learning in nonalcoholic fatty liver disease diagnosis: genetic based artificial neural networks.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease in the world. The NAFLD spectrum includes simple st...

TwinEDA: a sustainable deep-learning approach for limb-position estimation in preterm infants' depth images.

Early diagnosis of neurodevelopmental impairments in preterm infants is currently based on the visual analysis of newborns' motion patterns by trained...

Direct Evaluation of Treatment Response in Brain Metastatic Disease with Deep Neuroevolution.

Cancer centers have an urgent and unmet clinical and research need for AI that can guide patient management. A core component of advancing cancer trea...

Gene-gene interaction detection with deep learning.

The extent to which genetic interactions affect observed phenotypes is generally unknown because current interaction detection approaches only conside...

Development of a multi-use decision support system for scientific management and breeding of sheep.

As the challenges of food insecurity and population explosion become more pressing, there is a dire need to revamp the existing breeding and animal ma...

Systems Drug Design for Muscle Invasive Bladder Cancer and Advanced Bladder Cancer by Genome-Wide Microarray Data and Deep Learning Method with Drug Design Specifications.

Bladder cancer is the 10th most common cancer worldwide. Due to the lack of understanding of the oncogenic mechanisms between muscle-invasive bladder ...

Abnormal amygdala functional connectivity and deep learning classification in multifrequency bands in autism spectrum disorder: A multisite functional magnetic resonance imaging study.

Previous studies have explored resting-state functional connectivity (rs-FC) of the amygdala in patients with autism spectrum disorder (ASD). However,...

Effectiveness of a Robot-Assisted Psychological Intervention for Children with Autism Spectrum Disorder.

Difficulties with social interaction characterise children with Autism Spectrum Disorders and have a negative impact in their everyday life. Integrati...

Intervention with a humanoid robot avatar for individuals with social anxiety disorders comorbid with autism spectrum disorders.

For some individuals with social anxiety disorders (SAD) comorbid with autism spectrum disorders (ASD), it is difficult to speak in front of others. H...

Identifying autism spectrum disorder in resting-state fNIRS signals based on multiscale entropy and a two-branch deep learning network.

BACKGROUND: The demand for early and precise identification of autism spectrum disorder (ASD) presented a challenge to the prediction of ASD with a no...

Review of Fundamental Active Current Extraction Techniques for SAPF.

The field of advanced digital signal processing methods is one of the fastest developing scientific and technical disciplines, and is important in the...

A deep learning approach to real-time HIV outbreak detection using genetic data.

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential...

Generation and Research of Online English Course Learning Evaluation Model Based on Genetic Algorithm Improved Neural Set Network.

The rationality and timeliness of the comprehensive results of English course learning quality are increasingly important in the process of modern edu...