Autism

Application of Artificial Neural Network and Genetic Algorithm Modeling for In Vitro Regeneration of Seaweed Seedling Production.

Marine macro-algae, commonly known as "seaweed," are used in everyday commodity products worldwide f...

Hematological Indices and Genetic Variants of Premature Ovarian Insufficiency: Machine Learning Approaches.

BACKGROUND: Premature Ovarian Insufficiency (POI) is associated with infertility. Little is known ab...

Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach.

BACKGROUND: The progressive cognitive decline, an integral component of Alzheimer's disease (AD), un...

What Legal Frameworks Should Govern Use of Genetic Test Results by Private Health Insurers in New Zealand?

The rising cost of private health insurance and constraints within public health systems are global ...

State of the Journal, 2023.

The American Journal of Occupational Therapy (AJOT) has maintained its top-ranking status in the fie...

ReGeNNe: genetic pathway-based deep neural network using canonical correlation regularizer for disease prediction.

MOTIVATION: Common human diseases result from the interplay of genes and their biologically associat...

Age-Specific Diagnostic Classification of ASD Using Deep Learning Approaches.

Autism Spectrum Disorder (ASD) is a highly heterogeneous condition, due to high variance in its etio...

Facilitating the Molecular Diagnosis of Rare Genetic Disorders Through Facial Phenotypic Scores.

With recent advances in computer vision, many applications based on artificial intelligence have bee...

Chatbot Artificial Intelligence for Genetic Cancer Risk Assessment and Counseling: A Systematic Review and Meta-Analysis.

PURPOSE: Most individuals with a hereditary cancer syndrome are unaware of their genetic status to u...

Automatically Predicting Perceived Conversation Quality in a Pediatric Sample Enriched for Autism.

Social interaction quality ratings derived from short natural conversations can differentiate childr...

GIRUS-net: A Multimodal Deep Learning Model Identifying Imaging and Genetic Biomarkers Linked to Alzheimer's Disease Severity.

We introduce an explainable deep neural architecture that combines brain structure with genetic infl...

Deep-Learning Markerless Tracking of Infant General Movements using Standard Video Recordings.

Monitoring spontaneous General Movements (GM) of infants 6-20 weeks post-term age is a reliable tool...

ChatGPT for phenotypes extraction: one model to rule them all?

Information Extraction (IE) is a core task in Natural Language Processing (NLP) where the objective ...

Context-Sensitive Common Data Models for Genetic Rare Diseases - A Concept.

Current challenges of rare diseases need to involve patients, physicians, and the research community...

A deep learning algorithm-based visual strategy intervention study for children with autism spectrum disorders - extraction and detection of children's behavioral features.

OBJECTIVE: Autism spectrum disorder is a group of neurodevelopmental disorders. The disease's etiolo...

Using machine learning to realize genetic site screening and genomic prediction of productive traits in pigs.

Genomic prediction, which is based on solving linear mixed-model (LMM) equations, is the most popula...

Recent application of artificial intelligence on histopathologic image-based prediction of gene mutation in solid cancers.

PURPOSE: Evaluation of genetic mutations in cancers is important because distinct mutational profile...

Application of modern computer technology in classical genetics lab course--Development of a mobile, lightweight and high-precision batch identification system for genetic traits of .

is a crucial biological experimental teaching material extensively utilized in experimental teachin...

Yield prediction through integration of genetic, environment, and management data through deep learning.

Accurate prediction of the phenotypic outcomes produced by different combinations of genotypes, envi...

AD-Syn-Net: systematic identification of Alzheimer's disease-associated mutation and co-mutation vulnerabilities via deep learning.

Alzheimer's disease (AD) is one of the most challenging neurodegenerative diseases because of its co...

Artificial Intelligence in the Genetic Diagnosis of Rare Disease.