Autism

Deep learning on genome-wide association studies to predict the patient-specific risk of radiation-induced erectile dysfunction.

OBJECTIVE: Radiation-induced erectile dysfunction (RIED) is a frequent, unpredictable complication following radiotherapy for prostate cancer. We hypothesized that genome wide genetic variants and clinical data could be analyzed using a novel deep learning model that incorporates known biological components to improve the patient-specific prediction of RIED risk. MATERIALS AND METHODS: Germline DN...

Integrative bioinformatics and machine learning identify shared molecular mechanisms and diagnostic biomarkers between Helicobacter pylori infection and atrial fibrillation.

BACKGROUND: Helicobacter pylori (H. pylori) infection and atrial fibrillation(AF) are major global health concerns. Emerging evidence has suggested a potentially chronic inflammation-mediated link between them, but the shared genetic mechanisms remain unclear. METHODS: We analyzed multidataset gene expression profiles from the Gene Expression Omnibus (GEO) database. Differential expression analysi...

An Emerging Role of Artificial Intelligence in Pediatric Neuroanesthesia.

Anesthesia for pediatric neurosurgery represents a highly complex and challenging field, characterized by age-dependent physiological variability, het...

Evaluating Public Sentiment on Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Compared With Other Mental Health Disorders From Posts on X (Formerly Known as Twitter): Longitudinal Analysis.

BACKGROUND: Neurodevelopmental disorders, especially attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), have seen a m...

Machine-enhanced reconstruction of functional connectomes unravels discriminative brain sub-systems in health and disease.

Reconstructing functional brain networks from functional Magnetic Resonance Imaging (fMRI) data typically relies on statistical pruning, where pairwis...

Linking rare variants to cell-type function in profound autism with brain transcriptomics and foundation models.

Genetic association studies have identified numerous genes harboring protein-disrupting variants in individuals with profound autism, but identifying ...

Artificial Intelligence in Personalized Breast Cancer Drug Safety: From Preclinical Toxicology to Clinical Risk Management.

PURPOSE: The artificial intelligence (AI) implementation in personalized medicine has transformed drug safety, especially in breast cancer treatment. ...

"Unpatients" in haemostasis and thrombosis. A yardstick of current paths in healthy carriers of a genetic susceptibility.

"Unpatients" are health-conscious individuals -carrying a genetic susceptibility whose impact is unclear with respect to the risk of a clinical event-...

Integrated multi-omics and experimental validation for identifying novel biomarkers of acute myocardial infarction.

Acute myocardial infarction (AMI) remains a leading cause of morbidity and mortality, and early diagnosis and personalized therapy are constrained by ...

FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep State Classification.

OBJECTIVE: Fetal sleep state classification is essential for identifying neurodevelopmental complications like hypoxia, but manual annotation is subje...

Impact of a personalized antidepressant prescription using genetics, socio-demographic and clinical data in major depressive disorder patients: A clinical study.

BACKGROUND: Major depressive disorder (MDD) is common and disabling, and antidepressant selection often follows a trial-and-error process. Predictix i...

Segmenting multi-modal abdominal multi-organ using the CADSTransN-Net model.

Deep learning advances medical imaging segmentation, but the insufficient diversity of datasets limits its performance. The AMOS22 dataset addresses t...

Feasibility and Acceptability of AI-Powered Tools for Early Autism Screening in Egypt: Semistructured Focus Group Study.

BACKGROUND: Autism spectrum disorder (ASD) is often underdiagnosed in low- and middle-income countries due to limited specialist access, sociocultural...

Hybrid deep learning and feature selection approach for autism detection from rs-fMRI data.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that is primarily characterized by deficits in social communication and restricted or...

Integrating generative AI and genetic causal inference identifies metformin as a repurposing candidate for normal tension glaucoma.

The normal tension glaucoma (NTG) has limited drug options since current antiglaucoma medications are mostly designed to decrease intraocular pressure...

mHealth-Enabled Stroke Screening for Pediatric Sickle Cell Disease in Low-Resource Settings: Systematic Literature Review of Critical Barriers, Emerging Technologies, and AI-Driven Solutions.

BACKGROUND: Sickle cell disease (SCD) is a genetic blood disorder affecting millions globally, with life-threatening complications, and most patients ...

Human Allele Frequency Distributions Contradict Current Narratives of Imminent Danger From Genetically Targeted Bioweapons.

Warnings of pathogens manufactured to target a specific ethnic group, so-called genetic bioweapons, have recently received considerable media attentio...

Challenges in translating AI-driven ASD/ADHD diagnosis: A methodological systematic review.

BACKGROUND: Early and accurate diagnosis of neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and attention-deficit/hypera...

Genome Database for Vaccinium: a knowledgebase for genetics, genomics, and breeding research.

The Genome Database for Vaccinium (GDV, https://www.vaccinium.org/) is a knowledgebase serving the global Vaccinium research community. GDV centralize...

Mapping whole-organism genetic comorbidities across model Species using unified ontologies.

Understanding how genetic variation contributes to organism-wide phenotypes is critical for identifying mechanisms of disease. Here, we present a comp...