AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Genetic Predisposition to Disease

Showing 151 to 160 of 261 articles

Clear Filters

Gene ontology enrichment analysis of congenital diaphragmatic hernia-associated genes.

Pediatric research
Congenital diaphragmatic hernia (CDH) is a commonly occurring major congenital anomaly with a profound impact on neonatal mortality. The etiology of CDH is poorly understood and is complicated by multiple clinical presentations, reflecting the locati...

Identification of novel immune-relevant drug target genes for Alzheimer's Disease by combining ontology inference with network analysis.

CNS neuroscience & therapeutics
AIMS: Alzheimer's disease (AD) is one of the leading causes of death in elderly people. Its pathogenesis is greatly associated with the abnormality of immune system. However, only a few immune-relevant AD drug target genes have been discovered up to ...

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk.

Nature genetics
Key challenges for human genetics, precision medicine and evolutionary biology include deciphering the regulatory code of gene expression and understanding the transcriptional effects of genome variation. However, this is extremely difficult because ...

Machine learning algorithm-based risk prediction model of coronary artery disease.

Molecular biology reports
In view of high mortality associated with coronary artery disease (CAD), development of an early predicting tool will be beneficial in reducing the burden of the disease. The database comprising demographic, conventional, folate/xenobiotic genetic ri...

Enabling Precision Medicine through Integrative Network Models.

Journal of molecular biology
A key challenge in precision medicine lies in understanding molecular-level underpinnings of complex human disease. Biological networks in multicellular organisms can generate hypotheses about disease genes, pathways, and their behavior in disease-re...

Network-based association analysis to infer new disease-gene relationships using large-scale protein interactions.

PloS one
Protein-protein interactions integrated with disease-gene associations represent important information for revealing protein functions under disease conditions to improve the prevention, diagnosis, and treatment of complex diseases. Although several ...

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy.

BMC bioinformatics
BACKGROUND: Spastic cerebral palsy (CP) is a leading cause of physical disability. Most people with spastic CP are born with it, but early diagnosis is challenging, and no current biomarker platform readily identifies affected individuals. The aim of...

Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.

Methods (San Diego, Calif.)
Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is s...