Autism

Predicting psychopathology symptom trajectories using machine learning: a 33-year prospective study.

BACKGROUND: While previous literature has established a link between psychopathology symptom trajectories and psychosocial risk, most studies have not extended into adulthood or incorporated comprehensive risk measures. We aimed to identify symptom trajectories for externalizing and internalizing symptoms over a 25-year span and predict them using machine learning. METHODS: We used data from a lon...

The gut microbiome in preterm infants: development, dysbiosis, and disease implications.

SUMMARYPreterm infants face a unique trajectory of gut microbiome assembly, shaped by the convergence of physiological immaturity, necessary clinical interventions, and the neonatal intensive care unit environment. This dysbiotic ecosystem-characterized by low diversity, depletion of beneficial commensals such as Bifidobacterium, and expansion of pathobionts, including Enterobacteriaceae-is increa...

Network-informed multi-trait genomic analysis decodes the shared genetic architecture and therapeutic landscape of pelvic floor disorders.

Pelvic floor disorders, including pelvic organ prolapse and urinary incontinence, represent a common health burden with substantial clinical comorbidi...

Artificial intelligence enables scale, consistency, and rigor in forensic identity inference.

Advances in forensic genomics, which include massively parallel sequencing, dense single nucleotide polymorphism testing, and forensic genetic genealo...

CME-KGDTI: integrating clustered mutations into knowledge graph embedding for drug-target interaction prediction.

BACKGROUND: Computational prediction of drug-target interaction (DTI) is critical for drug discovery and precision medicine. Herein, we constructed a ...

Anna vs. Judith: A randomized comparison of AI-delivered psychodynamic and cognitive behavioral therapies for social anxiety disorder.

Artificial intelligence (AI) offers a potential solution to the scalability limits of internet-based psychological interventions. This randomized cont...

ADHD medications and preadolescent brain structure: patterns of cortical attenuation from the ABCD study.

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in the U.S. Amphetamine (AMP), methylphenidate (MPH), a...

Machine learning-based gait classification and genome-wide association identify a QTL for gait type in Colombian paso horses.

Coordinated mammalian locomotion relies on spinal circuits where DMRT3 regulates strides and alternative gaits. However, DMRT3 does not explain differ...

Fine-grained classroom behavior monitoring for students with special education needs: an audiovisual fusion approach to posture analysis.

A core challenge of inclusive education lies in the difficulty teachers face in effectively identifying and responding to the diverse behavioral manif...

An Interpretable Machine Learning Model for Predicting Intellectual Disability in Children With Cerebral Palsy.

BACKGROUND: Intellectual disability (ID) affects approximately 45% of children with cerebral palsy (CP), yet early identification is frequently hinder...

Combinations of single gene predictors with AI-driven polygenic precision therapies in cardiovascular diseases.

Pharmacogenomics (PGx) is transforming how we treat cardiovascular disease (CVD) by enabling us to select and dose drugs based on our genetic profiles...

Multi-Omics Integration Reveals the Genetic Mechanisms of Periodontitis and Predicts Therapeutic Drugs.

BACKGROUND: Periodontitis is a chronic inflammatory disease driven by host immune dysregulation. However, the specific genetic regulatory mechanisms u...

Listening forward: emerging roles of bioacoustics in ecology, evolution, and conservation.

Bioacoustics is increasingly shifting from a mostly descriptive pursuit to one that can anticipate ecological change. Recent innovations-from autonomo...

TKOA-GPNN: a model framework for genotype-to-phenotype prediction in Duroc pigs.

CONTEXT: Genomic prediction has been established as a powerful tool in pig breeding, which typically entails the analysis of large-scale genomic datas...

Graph Neural Networks and sequential architectures for autism detection from eye-tracking biomarkers: a multi-site study.

BACKGROUND: Autism Spectrum Disorder (ASD) affects 1 in 100 children globally, yet early detection remains challenging due to reliance on subjective b...

Ketone Body Metabolism and Sodium Glucose Cotransporter 2 Inhibitor Response in Heart Failure With Ischemic Cause: A Precision Medicine Approach Using Metabolomics Integration With Global Burden of Disease Population Data Across Diverse Genetic Backgrounds.

BACKGROUND: Heart failure with ischemic cause is associated with substantial cardiovascular mortality. SGLT2 (sodium glucose cotransporter 2) inhibito...

MIRAGE: a multimodal deep learning framework for interpretable risk assessment of high myopia from genetic and retinal imaging data.

High myopia (HM) is a complex condition influenced by both genetic and environmental factors, yet its early prediction and clinical intervention remai...

AI'm Here to Help: Enhancing Laboratory Genetic Counseling with Artificial Intelligence.

BACKGROUND: Artificial intelligence (AI) is transforming the fields of genetics and genetic counseling, enhancing both clinical and laboratory practic...

Machine learning model to identify gut microbiome-derived metabolites as potential biomarkers of autism spectrum disorder: a pilot study.

Autism Spectrum Disorder (ASD) arises from complex and not yet completely understood interactions between genetic and environmental factors. Alongside...

Enhance autism spectrum disorder detection using stacking ensemble learning model with explainable AI.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is manifested by sensory abnormalities such as hypersensitivity to sound and touc...