AI Medical Compendium Topic

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

Genetic Association Studies

Showing 51 to 60 of 90 articles

Clear Filters

StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis.

BMC genomics
BACKGROUND: Recently, a number of studies have been conducted to investigate how plants respond to stress at the cellular molecular level by measuring gene expression profiles over time. As a result, a set of time-series gene expression data for the ...

Analysis of disease comorbidity patterns in a large-scale China population.

BMC medical genomics
BACKGROUND: Disease comorbidity is popular and has significant indications for disease progress and management. We aim to detect the general disease comorbidity patterns in Chinese populations using a large-scale clinical data set.

Artificial intelligence in clinical and genomic diagnostics.

Genome medicine
Artificial intelligence (AI) is the development of computer systems that are able to perform tasks that normally require human intelligence. Advances in AI software and hardware, especially deep learning algorithms and the graphics processing units (...

High-throughput phenotyping with deep learning gives insight into the genetic architecture of flowering time in wheat.

GigaScience
BACKGROUND: Measurement of plant traits with precision and speed on large populations has emerged as a critical bottleneck in connecting genotype to phenotype in genetics and breeding. This bottleneck limits advancements in understanding plant genome...

A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data.

BMC medical genomics
BACKGROUND: Dementia with Lewy bodies (DLB) is the second most common subtype of neurodegenerative dementia in humans following Alzheimer's disease (AD). Present clinical diagnosis of DLB has high specificity and low sensitivity and finding potential...

HPO2Vec+: Leveraging heterogeneous knowledge resources to enrich node embeddings for the Human Phenotype Ontology.

Journal of biomedical informatics
BACKGROUND: In precision medicine, deep phenotyping is defined as the precise and comprehensive analysis of phenotypic abnormalities, aiming to acquire a better understanding of the natural history of a disease and its genotype-phenotype associations...

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk.

Nature genetics
We address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts the specific regulatory effects and the deleterious impact of genetic variants. Applying this framework to 1,7...

New Deep Learning Genomic-Based Prediction Model for Multiple Traits with Binary, Ordinal, and Continuous Phenotypes.

G3 (Bethesda, Md.)
Multiple-trait experiments with mixed phenotypes (binary, ordinal and continuous) are not rare in animal and plant breeding programs. However, there is a lack of statistical models that can exploit the correlation between traits with mixed phenotypes...

Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs.

PLoS computational biology
Increasing evidence has indicated that microRNAs(miRNAs) play vital roles in various pathological processes and thus are closely related with many complex human diseases. The identification of potential disease-related miRNAs offers new opportunities...