Autism

Canalization of neural dynamics by δ-protocadherins in the developing zebrafish optic tectum.

Brain dynamics are constrained by the underlying topology of neuronal networks. How genes collaborate to organize these neural networks during development remains an enduring mystery. In humans, large numbers of genes have been implicated in neurodevelopmental disorders that are characterized by variable and overlapping phenotypes. The complexity of the brain and the heterogeneity of the disorders...

Applying natural language processing and large language models to clinical notes for phenotyping and diagnosing rare diseases: a systematic review.

OBJECTIVES: Patients with rare diseases often face long delays before receiving a diagnosis. Using electronic health records for automated phenotyping and diagnosis of rare diseases is a promising approach but can be challenging because critical information is often recorded in unstructured notes rather than structured fields. This systematic review synthesizes the current literature applying natu...

Analysis of electroencephalogram microstates and spectral power in children and adolescents with attention deficit hyperactivity disorder.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a widely recognized neurodevelopmental disorder characterized by inattention, hyperactivity, and im...

Machine learning-based screening model for Tic disorders comorbid with attention-deficit/hyperactivity disorder in children and SHAP value interpretation: a retrospective observational study.

Tic disorders (TD) are common neurodevelopmental conditions in children and adolescents, characterized primarily by motor and vocal tics, with heterog...

Machine learning-based prediction of intellectual disability in children with autism spectrum disorder: using behavioral observation techniques.

PURPOSE: To construct and evaluate a LightGBM prediction model for intellectual disabilities in children with Autism Spectrum Disorder (ASD). METHODS:...

Autism spectrum disorder identification using machine learning models on MRI data.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects sensory processing, speech, behavior and identifying the condition at an...

Translating transcriptomics analysis into diagnostic workflows: clinical variant identification and interpretation in hypothesis-driven and hypothesis-free approaches.

BACKGROUND: Despite significant advancements in genetic diagnosis, there are still bottlenecks in DNA-level testing. Challenges to diagnosis include t...

2NPLGBM: a genomic model that merges the strengths of classical and machine learning methods in genomic prediction.

BACKGROUND: Genomic prediction (GP) is a central component of modern plant breeding, enabling the early selection of superior genotypes based on genom...

Capsid Engineering of Adeno-Associated Viruses for Targeted Gene Therapy in Kidney Diseases.

The global burden of chronic and genetic kidney diseases poses a significant challenge to healthcare systems. Current therapies, including dialysis, t...

Predictors of warfarin therapeutic dose across thromboembolic indications: an exploratory early clinical evaluation study using machine learning-integrated explainable artificial intelligence and Bayesian models.

BACKGROUND: Warfarin dosing varies widely due to genetic, demographic, and clinical factors, but it is unknown whether the importance, equilibrium and...

From Three to Eight Clusters: A Machine Learning-Based Classification of Operated Adult Spinal Deformity Patients.

BACKGROUND: Adult spinal deformity (ASD) is a heterogeneous condition encompassing diverse etiologies, clinical presentations, and surgical challenges...

Automating genomic reanalysis: perspectives of people living with, or impacted by, a genetic, rare or undiagnosed condition.

BACKGROUND: Reanalysis - the process of re-examining a person's existing genomic data based on new knowledge or technology - has the potential to grea...

Quantum Machine Learning for Biomedical Classification Problems: A Feasibility Study on Real Quantum Hardware.

PURPOSE: Recent advances in quantum computing offer opportunities to explore alternative methods for the solution of classification problems commonly ...

Genome-Wide Association Study and Fine Mapping Uncover Key Genetic Loci and Credible Genes of Intracranial Aneurysm and Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: Intracranial aneurysm (IA) is a common neurovascular disorder; rupture causes aneurysmal subarachnoid hemorrhage with high mortality. Desp...

Gene-Environment Interactions in Predicting Self-Harm: A Machine Learning Approach Using Explainable Artificial Intelligence.

BACKGROUND: Self-harm is a critical public health concern; nevertheless, the complex interplay between genetic predispositions and environmental facto...

Hybrid EEG Feature Fusion Framework for Accurate Autism Spectrum Disorder Diagnosis Using Ensemble Learning.

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition with increasing global prevalence and no standardized biological test for ear...

Integrated cell-free DNA and omics genetic scores for early detection of gestational diabetes: evidence from a nationwide multicenter study.

BACKGROUND: Gestational diabetes mellitus (GDM) affects 15.6% of pregnancies globally, with Vietnam exhibiting one of the highest prevalences at 21%. ...

CWAGS: multi-trait genomic selection using channel weighted attention convolutional network.

BACKGROUND: Genomic selection serves as an effective approach to accelerate the improvement of agronomic traits in crops. However, as a core technique...

Multi-dimensional risk prediction and genetic architecture of aspiration pneumonia: a population-based analysis.

BACKGROUND: Aspiration pneumonia represents a significant but understudied cause of morbidity and mortality, particularly among aging populations with...

Integrative advances in biomarker-driven prostate cancer management from genomic discovery to precision oncology.

Prostate cancer (PCa) is the second most common malignancy in men worldwide, with rising mortality linked to late-stage diagnoses. While current diagn...