Autism

Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis.

Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide association studies, a complete genetic and molecular understanding of MI is elusive and needs to be fully explored. This study aimed to elucidate the genetic framework of MI and explore the potential health benefits of natural compounds (NCs). The genetic architecture of MI was explored using data...

DeepASD: a deep adversarial-regularized graph learning method for ASD diagnosis with multimodal data.

Autism Spectrum Disorder (ASD) is a prevalent neurological condition with multiple co-occurring comorbidities that seriously affect mental health. Precisely diagnosis of ASD is crucial to intervention and rehabilitation. A single modality may not fully reflect the complex mechanisms underlying ASD, and combining multiple modalities enables a more comprehensive understanding. Here, we propose, Deep...

Bilinear Perceptual Fusion Algorithm Based on Brain Functional and Structural Data for ASD Diagnosis and Regions of Interest Identification.

Autism spectrum disorder (ASD) is a serious mental disorder with a complex pathogenesis mechanism and variable presentation among individuals. Althoug...

Machine learning phenotyping and GWAS reveal genetic basis of Cd tolerance and absorption in jute.

Cadmium (Cd) is a dangerous environmental contaminant. Jute (Corchorus sp.) is an important natural fiber crop with strong absorption and excellent ad...

The transformative potential of AI-driven CRISPR-Cas9 genome editing to enhance CAR T-cell therapy.

This narrative review examines the promising potential of integrating artificial intelligence (AI) with CRISPR-Cas9 genome editing to advance CAR T-ce...

Leveraging AI for the diagnosis and treatment of autism spectrum disorder: Current trends and future prospects.

The integration of artificial intelligence (AI) into the diagnosis and treatment of autism spectrum disorder (ASD) represents a promising frontier in ...

A machine learning model for early diagnosis of type 1 Gaucher disease using real-life data.

OBJECTIVE: The diagnosis of Gaucher disease (GD) presents a major challenge due to the high variability and low specificity of its clinical characteri...

Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection.

Utilities face serious obstacles from power theft, which calls for creative ways to maintain income and improve operational effectiveness. This study ...

Exploration of the prediction and generation patterns of heterocyclic aromatic amines in roast beef based on Genetic Algorithm combined with Support Vector Regression.

Heterocyclic aromatic amines (HAAs) are harmful byproducts in food heating. Therefore, exploring the prediction and generation patterns of HAAs is of ...

Fractional whale driving training-based optimization enabled transfer learning for detecting autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a neurological illness that degrades communication and interaction among others. Autism can be detected at any stage...

Comparison of machine learning methods for genomic prediction of selected Arabidopsis thaliana traits.

We present a comparison of machine learning methods for the prediction of four quantitative traits in Arabidopsis thaliana. High prediction accuracies...

A genetic algorithm-based method to modulate the difficulty of serious games along consecutive robot-assisted therapy sessions.

BACKGROUND AND OBJECTIVE: One of the biggest challenges during neurorehabilitation therapies is finding an appropriate level of therapy intensity for ...

What could be the role of genetic tests and machine learning of AXIN2 variant dominance in non-syndromic hypodontia? A case-control study in orthodontically treated patients.

BACKGROUND: Hypodontia is the most prevalent dental anomaly in humans, and is primarily attributed to genetic factors. Although genome-wide associatio...

A machine learning enhanced EMS mutagenesis probability map for efficient identification of causal mutations in Caenorhabditis elegans.

Chemical mutagenesis-driven forward genetic screens are pivotal in unveiling gene functions, yet identifying causal mutations behind phenotypes remain...

MAGICAL: A multi-class classifier to predict synthetic lethal and viable interactions using protein-protein interaction network.

Synthetic lethality (SL) and synthetic viability (SV) are commonly studied genetic interactions in the targeted therapy approach in cancer. In SL, inh...

Characterizing Autism Spectrum Disorder Through Fusion of Local Cortical Activation and Global Functional Connectivity Using Game-Based Stimuli and a Mobile EEG System.

The deficit in social interaction skills among individuals with autism spectrum disorder (ASD) is strongly influenced by personal experiences and soci...

Hybrid similarity based feature selection and cascade deep maxout fuzzy network for Autism Spectrum Disorder detection using EEG signal.

Autism Spectrum Disorder (ASD) is a neurological disorder that influences a person's comprehension and way of behaving. It is a lifetime disability th...

Separating group- and individual-level brain signatures in the newborn functional connectome: A deep learning approach.

Recent studies indicate that differences in cognition among individuals may be partially attributed to unique brain wiring patterns. While functional ...

Gait pattern modification based on ground contact adaptation using the robot-assisted training platform (RATP).

Robot-assisted rehabilitation and training systems are utilized to improve the functional recovery of individuals with mobility limitations. These sys...

Beyond hand-crafted features for pretherapeutic molecular status identification of pediatric low-grade gliomas.

The use of targeted agents in the treatment of pediatric low-grade gliomas (pLGGs) relies on the determination of molecular status. It has been shown ...