Autism

Exploring the application of AI in the education of children with autism: a public health perspective.

INTRODUCTION: Autism Spectrum Disorder (ASD) presents significant challenges in social communication and interaction, critically impacting the lives of children with ASD. Traditional interventions, such as Applied Behavior Analysis (ABA) and Social Skills Training (SST), have been widely used to address social skill deficits in these children. While these methods are effective, they often require ...

Identifying autism spectrum disorder based on machine learning for multi-site fMRI.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by repetitive stereotypical behavior and social impairment. Early diagnosis is essential for developing a treatment plan for autism. Although multi-site data can expand the dataset to facilitate the process of data analysis, data heterogeneity between sites and the large amount of data make data analysis diff...

Intestinal Microbiome Modulation of Therapeutic Efficacy of Cancer Immunotherapy.

Bacteria are associated with certain cancers and may induce genetic instability and cancer progression. The gut microbiome modulates the response to c...

Analysis of the genetic basis of fiber-related traits and flowering time in upland cotton using machine learning.

Cotton is an important crop for fiber production, but the genetic basis underlying key agronomic traits, such as fiber quality and flowering days, rem...

Assessment of glymphatic function and white matter integrity in children with autism using multi-parametric MRI and machine learning.

OBJECTIVES: To assess glymphatic function and white matter integrity in children with autism spectrum disorder (ASD) using multi-parametric MRI, combi...

Modeling gene interactions in polygenic prediction via geometric deep learning.

Polygenic risk score (PRS) is a widely used approach for predicting individuals' genetic risk of complex diseases, playing a pivotal role in advancing...

Multimodal multiview bilinear graph convolutional network for mild cognitive impairment diagnosis.

Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's disease (AD) and can serve as an important indicato...

Automated karyogram analysis for early detection of genetic and neurodegenerative disorders: a hybrid machine learning approach.

Anomalous chromosomes are the cause of genetic diseases such as cancer, Alzheimer's, Parkinson's, epilepsy, and autism. Karyotype analysis is the stan...

Proximity-based solutions for optimizing autism spectrum disorder treatment: integrating clinical and process data for personalized care.

Autism Spectrum Disorder (ASD) affects millions of individuals worldwide, presenting challenges in social communication, repetitive behaviors, and sen...

Unlocking autism's complexity: the e Initiative's path to comprehensive motor function analysis.

The long-standing practice of using manualized inventories and observational assessments to diagnose and track motor function in autism overlooks crit...

Perspective: Multiomics and Artificial Intelligence for Personalized Nutritional Management of Diabetes in Patients Undergoing Peritoneal Dialysis.

Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects of dietary glucose, glucose from dialysate, and o...

An Intelligent Prediction Model for the Synthesis Conditions of Metal-Organic Frameworks Utilizing Artificial Neural Networks Enhanced by Genetic Algorithm Optimization.

In the field of emerging materials, metal-organic frameworks (MOFs) have gained prominence due to their unique porous structures, showing versatility ...

Multiple, Single Trait GWAS and Supervised Machine Learning Reveal the Genetic Architecture of Fraxinus excelsior Tolerance to Ash Dieback in Europe.

Common ash (Fraxinus excelsior) is under intensive attack from the invasive alien pathogenic fungus Hymenoscyphus fraxineus, causing ash dieback at ep...

Highlights of Precision Medicine, Genetics, Epigenetics and Artificial Intelligence in Pompe Disease.

Pompe disease is a neuromuscular disorder caused by a deficiency of the enzyme acid alpha-glucosidase (), which leads to lysosomal glycogen accumulati...

Convolutional neural network (CNN) configuration using a learning automaton model for neonatal brain image segmentation.

CNN is considered an efficient tool in brain image segmentation. However, neonatal brain images require specific methods due to their nature and struc...

An unconventional separation method of α-Terpineol from its isomer 1,8-Cineole via in situ-association formation of deep eutectic solvent and machine learning.

α-Terpineol and 1,8-cineole are two important compounds in essential oils. This study developed an efficient method to recover α-terpineol from model ...

An ensemble deep learning framework for energy demand forecasting using genetic algorithm-based feature selection.

Accurate energy demand forecasting is critical for efficient energy management and planning. Recent advancements in computing power and the availabili...

The Role of Artificial Intelligence in Health Care.

Artificial intelligence (AI) plays a leading role in transmuting the field of healthcare. Numerous aspects of AI have been incorporated into the healt...

AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks.

Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, and controlling the complex behavior of chem...

Blood cancer prediction model based on deep learning technique.

Blood cancer is among the critical health concerns among people around the world and normally emanates from genetic and environmental issues. Early de...