AIMC Topic: Phenotype

Clear Filters Showing 61 to 70 of 1034 articles

Developing a Behavioral Phenotyping Layer for Artificial Intelligence-Driven Predictive Analytics in a Digital Resiliency Course: Protocol for a Randomized Controlled Trial.

JMIR research protocols
BACKGROUND: Digital interventions for mental health are pivotal for addressing barriers such as stigma, cost, and accessibility, particularly for underserved populations. While the effectiveness of digital interventions has been established, poor adh...

In silico prediction of variant effects: promises and limitations for precision plant breeding.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Sequence-based AI models show great potential for prediction of variant effects at high resolution, but their practical value in plant breeding remains to be confirmed through rigorous validation studies. Plant breeding has traditionally relied on ph...

Genetic analyses of eight complex diseases using predicted continuous representations of disease.

Cell reports methods
We evaluated whether predicted continuous disease representations could enhance genetic discovery beyond case-control genome-wide association study (GWAS) phenotypes across eight complex diseases in up to 485,448 UK Biobank participants. Predicted ph...

Advances in machine learning for ABCA4-related retinopathy: segmentation and phenotyping.

International ophthalmology
PURPOSE: Stargardt disease, also called ABCA4-related retinopathy (ABCA4R), is the most common form of juvenile-onset macular dystrophy and yet lacks an FDA approved treatment. Substantial progress has been made through landmark studies like that of ...

Extensive novel diversity and phenotypic associations in the dromedary camel microbiome are revealed through deep metagenomics and machine learning.

PloS one
The dromedary camel, also known as one-humped camel or Arabian camel, is iconic and economically important to Arabian society. Its contemporary importance in commerce and transportation, along with the historical and modern use of its milk and meat p...

Predicting treatment-seeking status for alcohol use disorder using polygenic scores and machine learning in a deeply-phenotyped sample.

Drug and alcohol dependence
BACKGROUND: Few individuals with alcohol use disorder (AUD) receive treatment. Previous studies have shown drinking behavior, psychological problems, and substance dependence to predict treatment seeking. However, to date, no studies have incorporate...

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

PloS one
BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation and treatment response. Identifying distinct subphenotypes of HTN may improve our understanding of its underlying mechanisms and guide more precise t...

Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry.

Nature communications
Aging heterogeneity in tissue-regenerative cells leads to variable therapeutic outcomes, complicating quality control and clinical predictability. Conventional analytical methods relying on labeling or cell lysis are destructive and incompatible with...

Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Trait Genome-to-Phenome (G2P) dimensionality and "breeding context" combine to influence the realised prediction skill of different whole genome prediction (WGP) methods. Theory and empirical evidence both suggest there is likely to be "No Free Lunch...