Autism

Decoding the Genetic Architecture of Acute Coronary Syndrome: A Review on Integrated Medical Modeling.

UNLABELLED: Genetic mutations contribute significantly to the complexity of understanding Acute Coronary Syndrome (ACS). Artificial Intelligence (AI) models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), have been integrated as an advanced approach to uncover hidden mutation clues for early detection and prevention of life-thr...

Systems-level multi-omics dissection of syndromic and idiopathic autism reveals distinct regulatory architectures, candidate molecular signatures, and potential therapeutic targets.

Biological systems operate as self-organizing information networks in which genetic, epigenetic, and regulatory interactions collectively determine functional outcomes. Autism encompasses a heterogeneous set of neurodevelopmental conditions, including syndromic and idiopathic subtypes. Despite extensive gene discovery efforts, how these autism subtypes differ in their underlying organization of bi...

Integrating artificial intelligence and machine learning into risk prediction for type 2 diabetes: A model for early identification of high-risk populations.

Family history, body mass index (BMI), and ethnicity are three key, well-established determinants of susceptibility to type 2 diabetes mellitus (T2DM)...

Cross-attention guided explainable deep transformer model for multi-level classification of rare neurological disorders using MRI images.

Neurological disorders (ND) impact a significant number of the population all over the world, affecting the brain, spinal cord, and peripheral nerves....

Associations between anterior hypothalamic subunits and ADHD and autistic traits revealed by deep learning MRI segmentation.

The hypothalamus is a central regulator of neuroendocrine function and social behavior, yet its internal organization has remained difficult to examin...

Evaluating Synthetic Anterior Segment Images for Transferable Eye Disease Recognition.

OBJECTIVE: To evaluate whether prompt-driven synthetic anterior segment disease (ASD) images preserve disease-relevant semantics for transferable ASD ...

Artificial Intelligence in Child and Adolescent Psychiatry: A Narrative Review of Recent Clinical Applications and Ethical Considerations.

PURPOSE OF REVIEW: This narrative review examines recent literature of artificial intelligence (AI) in child and adolescent psychiatry. With increasin...

Diagnosis of ADHD in children from EEG signals using amplitude modulation features.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children and accurate diagnosis of this disorde...

Pathway-level epigenetic modeling illuminates the methylation architecture to asthma risk across tissues.

BACKGROUND: Asthma is a clinically heterogeneous airway disorder characterized by complex interactions between environmental exposures, immune activat...

Incorporating dietary information to enhance polygenic prediction models with applications to body mass index and type 2 diabetes.

BACKGROUND: Polygenic predictors can enhance screening for metabolism-related traits such as body mass index (BMI) and type 2 diabetes (T2D). However,...

Engineered small extracellular vesicles in hematologic malignancies: mechanisms, therapeutic strategies, and translational challenges.

Hematologic malignancies remain among the most challenging cancers to treat due to genetic heterogeneity, clonal evolution, and therapy resistance. Ex...

GENIE: A Two-Stage Interpretable Deep Learning Framework for Revealing the High-Order Genetic Interaction Network of Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive impairment and memory loss. The underlying mechanisms ...

E-InfertilityTest: Implementing an explainable AI framework for male infertility assessment.

Male infertility has emerged as a significant concern in modern society, with genetic defects as one of the major underlying cause behind it. This imp...

Artificial Intelligence-Driven Multimodal Prediction of 10-Year Incident Glaucoma Integrating Genetic and Deep Learning-Derived Imaging Features.

PURPOSE: Glaucoma is the leading cause of irreversible blindness worldwide. It often remains asymptomatic until advanced stages. Hence, accurate predi...

Interaction Between Air Pollution and Genetic Predisposition to Blood Pressure and LDL-C on Cardiovascular Events.

AIMS: Particulate matter ≤2.5μm (PM2.5) air pollution is a leading global environmental risk factor. We investigated the impact of PM2.5 on cardiovasc...

Machine Learning-Based Identification of Distinct Risk Factors for Moderate vs Severe Proximal Junctional Kyphosis After Adult Spinal Deformity Surgery.

BACKGROUND CONTEXT: Proximal junctional kyphosis (PJK) is a well-recognized complication of adult spinal deformity (ASD) surgery. However, traditional...

Prenatal exposure to residential greenness and artificial light at night and neurodevelopmental outcomes in children aged 4-12 years: A retrospective cohort study in China.

BACKGROUND: Neurodevelopmental outcomes may be shaped by modifiable residential environmental exposures during pregnancy; however, in rapidly urbanizi...

Machine Diagnostics and Machine Phenotyping of Migraine: A HUNT Study.

BACKGROUND AND OBJECTIVES: In the absence of biomarkers, the true biological footprint of migraine remains incompletely understood. It could perhaps b...

Integrative analysis of mortality risk in SFTS using machine learning and genetic approaches.

This study presents a novel approach to predicting mortality risk in patients with severe fever with thrombocytopenia syndrome (SFTS) by integrating m...

Parents' perspectives on the use of artificial intelligence chatbots to promote physical activity among individuals with autism spectrum disorder.

Purpose: Advances in artificial intelligence (AI) have led to the increasing use of chatbots to promote physical activity (PA) through personalised gu...