Autism

An Interpretable Sparse Graph Contrastive Learning Approach for Identifying Breast Cancer Risk Variants

Genome-wide association studies (GWASs) have identified over 2,400 genetic variants associated to breast cancer. Conventional GWASs methods that analyze variants independently often overlook the complex genetic interactions underlying disease susceptibility. Machine and deep learning approaches present promising alternatives, yet encounter challenges, including overfitting due to high dimensionali...

Identification of novel vertebral development factors through UK Biobank driven genetic and body imaging analysis reveals markers for back pain

Numerical variations and transitional anatomy in the human vertebral column, observed in up to 36% of individuals, represent a significant yet understudied aspect of skeletal development with potential effects on multiple physiological systems. Utilising UK Biobank data, we integrated genetic analysis with deep learning-based multi-modal body imaging to investigate genetic factors associated with ...

Leveraging hierarchical structures for genetic block interaction studies using the hierarchical transformer

Initially introduced in 1909 by William Bateson, classic epistasis (genetic variant interaction) refers to the phenomenon that one variant prevents an...

A Case for Automated Segmentation of MRI Data in Milder Neurodegenerative Diseases

Volumetric analysis and segmentation of magnetic resonance imaging (MRI) data is an important tool for evaluating neurological disease progression and...

Assessing Genotype-Phenotype Correlations with Deep Learning in Colorectal Cancer: A Multi-Centric Study

Deep Learning (DL) has emerged as a powerful tool to predict genetic biomarkers directly from digitized Hematoxylin and Eosin (H&E) slides in colorect...

MUTATE: A Human Genetic Atlas of Multi-organ AI Endophenotypes using GWAS Summary Statistics

Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide intermediate phenotypes (i.e., endophenotypes) that bri...

Evaluation of Machine Learning and Traditional Statistical Models to Assess the Value of Stroke Genetic Liability for Prediction of Risk of Stroke within the UK Biobank

Stroke is one of the leading causes of mortality and long-term disability in adults over 18 years of age globally and its increasing incidence has bec...

Data-Driven Early Prediction of Cerebral Palsy Using AutoML and interpretable kinematic features

Early identification of cerebral palsy (CP) remains a major challenge due to the reliance on expert assessments that are time-intensive and not scalab...

Comparative Medical Ecology of Gut Microbiomes in Major Neurodegenerative, Neurodevelopmental, and Psychiatric (NNP) Disorders

This study provides a comprehensive medical ecology analysis of gut microbiome alterations in four neuropsychiatric disorders: Alzheimer’s disease (AD...

Data-driven consideration of genetic disorders for global genomic newborn screening programs

Over 30 international studies are exploring newborn sequencing (NBSeq) to expand the range of genetic disorders included in newborn screening. Substan...

Genetic variants risk assessment for Long QT Syndrome through machine learning and multielectrode array recordings

Long QT syndrome (LQTS) is a life-threatening genetic disorder characterized by prolonged QT intervals on electrocardiograms. Congenital forms are mos...

EIRsurvival: Deep Learning-based time-to-event analysis on high-dimensional genotype and multi-omics data

Time-to-event data in disease occurrence is often right-censored, requiring survival models for accurate predictions. While deep learning advancements...

Analysis of genetic overlap between inborn errors of immunity and neurodevelopmental disorders

Inborn errors of immunity (IEI), formerly known as primary immune deficiencies (PID), are a group of genetic disorders that affect the immune system, ...

Genetic Architecture and Risk Prediction of Gestational Diabetes Mellitus in over 116,144 Chinese Pregnancies

Gestational diabetes mellitus (GDM), a heritable metabolic disorder and the most common pregnancy-related condition, remains understudied regarding it...

Encoding of pretrained large language models mirrors the genetic architectures of human psychological traits

Recent advances in large language models (LLMs) have prompted a frenzy in utilizing them as universal translators for biomedical terms. However, the b...

AI-Driven Fluorescence Peak Analysis for Chromosomal Aneuploidy Detection: A Python-Based Machine Learning Approach for Enhanced Accuracy and Efficiency

Chromosomal aneuploidy, a condition characterized by an abnormal number of chromosomes, is a major genetic disorder affecting human reproduction, lead...

Finding the Forest in the Trees: Using Machine Learning and Online Cognitive and Perceptual Measures to Predict Adult Autism Diagnosis

Traditional subjective measures are limited in the insight they provide into underlying behavioral differences associated with autism and, accordingly...

Patient-centered Evaluation of AI Answers to Genetic Counseling Questions

The growing use of large language models for health communication raises important questions about patient preferences, trust, and satisfaction with A...

Unmet Needs in Acute Hepatic Porphyria Diagnosis: A Comparative Big Data Analysis of an AI-based Human-in-the-Loop Screening Versus Standard of Care

Acute Hepatic Porphyria (AHP) is a rare genetic disease characterized by unpredictable life-threatening attacks. There is no reliable biochemical scre...

Artificial Intelligence for Chronic Kidney Disease Early Detection and Prognosis

The integration of Artificial Intelligence (AI) in the early detection and prognosis of Chronic Kidney Disease (CKD) is revolutionizing nephrology by ...