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Genetic Predisposition to Disease

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Unsupervised Clustering of Missense Variants in HNF1A Using Multidimensional Functional Data Aids Clinical Interpretation.

American journal of human genetics
Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes ris...

Genomic risk scores for juvenile idiopathic arthritis and its subtypes.

Annals of the rheumatic diseases
OBJECTIVES: Juvenile idiopathic arthritis (JIA) is an autoimmune disease and a common cause of chronic disability in children. Diagnosis of JIA is based purely on clinical symptoms, which can be variable, leading to diagnosis and treatment delays. De...

Relation of vitamin D and BsmI variant with temporomandibular diseases in the Turkish population.

The British journal of oral & maxillofacial surgery
Vitamin D (VD) levels and several variants in the vitamin D receptor (VDR) gene are associated with the occurrence of diseases of the bones and cartilage. The aim of this research was to study and compare the association of the BsmI variant in the VD...

Assessment of and polymorphisms in age-related macular degeneration using classic and machine-learning approaches.

Ophthalmic genetics
BACKGROUND: and are pivotal genes driving increased risk for age-related macular degeneration (AMD) among several populations. Here, we performed a hospital-based case-control study to evaluate the effects of three single nucleotide polymorphisms (...

An ensemble approach for CircRNA-disease association prediction based on autoencoder and deep neural network.

Gene
Circular RNAs (circRNA) are a special kind of covalently closed single-stranded RNA molecules. They have been shown to control and coordinate various biological processes. Recent researches show that circRNAs are closely associated with numerous chro...

Functional fine-mapping of noncoding risk variants in amyotrophic lateral sclerosis utilizing convolutional neural network.

Scientific reports
Recent large-scale genome-wide association studies have identified common genetic variations that may contribute to the risk of amyotrophic lateral sclerosis (ALS). However, pinpointing the risk variants in noncoding regions and underlying biological...

Predicting breast cancer risk using interacting genetic and demographic factors and machine learning.

Scientific reports
Breast cancer (BC) is a multifactorial disease and the most common cancer in women worldwide. We describe a machine learning approach to identify a combination of interacting genetic variants (SNPs) and demographic risk factors for BC, especially fac...

A Knowledge-Based Machine Learning Approach to Gene Prioritisation in Amyotrophic Lateral Sclerosis.

Genes
Amyotrophic lateral sclerosis is a neurodegenerative disease of the upper and lower motor neurons resulting in death from neuromuscular respiratory failure, typically within two to five years of first symptoms. Several rare disruptive gene variants h...

A novel graph attention adversarial network for predicting disease-related associations.

Methods (San Diego, Calif.)
Identifying complex human diseases at molecular level is very helpful, especially in diseases diagnosis, therapy, prognosis and monitoring. Accumulating evidences demonstrated that RNAs are playing important roles in identifying various complex human...

PopPhy-CNN: A Phylogenetic Tree Embedded Architecture for Convolutional Neural Networks to Predict Host Phenotype From Metagenomic Data.

IEEE journal of biomedical and health informatics
Accurate prediction of the host phenotype from a metagenomic sample and identification of the associated microbial markers are important in understanding potential host-microbiome interactions related to disease initiation and progression. We introdu...