Autism

Early Prediction of Alzheimer's and Related Dementias: A Machine Learning Approach Utilizing Social Determinants of Health Data

Alzheimer's disease and related dementias (AD/ADRD) represent a growing healthcare crisis affecting over 6 million Americans. While genetic factors play a crucial role, emerging research reveals that social determinants of health (SDOH) significantly influence both the risk and progression of cognitive functioning, such as cognitive scores and cognitive decline. This report examines how these so...

A Foundation Model for Patient Behavior Monitoring and Suicide Detection

Foundation models (FMs) have achieved remarkable success across various domains, yet their adoption in healthcare remains limited. While significant advances have been made in medical imaging, genetic biomarkers, and time series from electronic health records, the potential of FMs for patient behavior monitoring through wearable devices remains underexplored. These datasets are inherently hetero...

Decision Tree Induction Through LLMs via Semantically-Aware Evolution

Decision trees are a crucial class of models offering robust predictive performance and inherent interpretability across various domains, including ...

ASD Classification on Dynamic Brain Connectome using Temporal Random Walk with Transformer-based Dynamic Network Embedding

Autism Spectrum Disorder (ASD) is a complex neurological condition characterized by varied developmental impairments, especially in communication an...

Learnable Group Transform: Enhancing Genotype-to-Phenotype Prediction for Rice Breeding with Small, Structured Datasets

Genotype-to-Phenotype (G2P) prediction plays a pivotal role in crop breeding, enabling the identification of superior genotypes based on genomic dat...

Identity Preserving Latent Diffusion for Brain Aging Modeling

Structural and appearance changes in brain imaging over time are crucial indicators of neurodevelopment and neurodegeneration. The rapid advancement...

Visual Attention Graph

Visual attention plays a critical role when our visual system executes active visual tasks by interacting with the physical scene. However, how to e...

A Neural Symbolic Model for Space Physics

In this study, we unveil a new AI model, termed PhyE2E, to discover physical formulas through symbolic regression. PhyE2E simplifies symbolic regres...

The 4D Human Embryonic Brain Atlas: spatiotemporal atlas generation for rapid anatomical changes using first-trimester ultrasound from the Rotterdam Periconceptional Cohort

Early brain development is crucial for lifelong neurodevelopmental health. However, current clinical practice offers limited knowledge of normal emb...

Language modelling techniques for analysing the impact of human genetic variation

Interpreting the effects of variants within the human genome and proteome is essential for analysing disease risk, predicting medication response, a...

MUTATE: a human genetic atlas of multiorgan artificial intelligence endophenotypes using genome-wide association summary statistics.

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

WheatGP, a genomic prediction method based on CNN and LSTM.

Wheat plays a crucial role in ensuring food security. However, its complex genetic structure and trait variation pose significant challenges for breed...

Toward Scalable Access to Neurodevelopmental Screening: Insights, Implementation, and Challenges

Children with neurodevelopmental disorders require timely intervention to improve long-term outcomes, yet early screening remains inaccessible in ma...

The order in speech disorder: a scoping review of state of the art machine learning methods for clinical speech classification

Background:Speech patterns have emerged as potential diagnostic markers for conditions with varying etiologies. Machine learning (ML) presents an op...

Autism Spectrum Disorder Detection Using Prominent Connectivity Features from Electroencephalography.

Autism Spectrum Disorder (ASD) is a disorder of brain growth with great variability whose clinical presentation initially shows up during early stages...

Deep Learning-based Brain Age Prediction Using MRI to Identify Fetuses with Cerebral Ventriculomegaly.

Fetal ventriculomegaly (VM) and its severity and associated central nervous system (CNS) abnormalities are important indicators of high risk for impai...

Machine Learning and Natural Language Processing to Improve Classification of Atrial Septal Defects in Electronic Health Records.

BACKGROUND: International Classification of Disease (ICD) codes can accurately identify patients with certain congenital heart defects (CHDs). In ICD-...

[Prophylactic surgery and genetic counselling: What impact of the artificial intelligence?].

In the area of cancer predisposition, certain situations may lead to the discussion of prophylactic surgery. This is rarely strictly recommended and d...

Forestwalk: A Machine Learning Workflow Brings New Insights Into Posture and Balance in Rodent Beam Walking.

The beam walk is widely used to study coordination and balance in rodents. While the task has ethological validity, the main endpoints of "foot slip c...

Hypergraph Multi-Modal Learning for EEG-based Emotion Recognition in Conversation

Emotional Recognition in Conversation (ERC) is an important method for diagnosing health conditions such as autism or depression, as well as underst...