The genetic architecture of biological age in nine human organ systems
Investigating the genetic underpinnings of human aging is essential for unraveling the
etiology of and developing actionable therapies for chronic diseases. Here, we characterize …
etiology of and developing actionable therapies for chronic diseases. Here, we characterize …
Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning
Abstract Machine learning has been increasingly used to obtain individualized
neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in …
neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in …
[HTML][HTML] Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures
Brain aging is a complex process influenced by various lifestyle, environmental, and genetic
factors, as well as by age-related and often co-existing pathologies. MRI and, more recently …
factors, as well as by age-related and often co-existing pathologies. MRI and, more recently …
[HTML][HTML] Neuroimaging-AI Endophenotypes of Brain Diseases in the General Population: Towards a Dimensional System of Vulnerability
Disease heterogeneity poses a significant challenge for precision diagnostics in both clinical
and sub-clinical stages. Recent work leveraging artificial intelligence (AI) has offered …
and sub-clinical stages. Recent work leveraging artificial intelligence (AI) has offered …
MUTATE: A Human Genetic Atlas of Multi-organ AI Endophenotypes using GWAS Summary Statistics
Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide
intermediate phenotypes (ie, endophenotypes) that bridge the genetics and clinical …
intermediate phenotypes (ie, endophenotypes) that bridge the genetics and clinical …
Accelerated brain age in young to early middle-aged adults after mild to moderate COVID-19 infection
SR Kesler, OY Franco-Rocha, A De La Torre Schutz… - medRxiv, 2024 - medrxiv.org
Cognitive decline is a common adverse effect of the Coronavirus Disease of 2019 (COVID-
19), particularly in the post-acute disease phase. The mechanisms of cognitive impairment …
19), particularly in the post-acute disease phase. The mechanisms of cognitive impairment …
AgeML: Age modelling with Machine Learning
J Garcia Condado, I Tellaetxe, J Cortes, A Erramuzpe - bioRxiv, 2024 - biorxiv.org
A successful approach to age modeling involves the supervised prediction of age using
machine learning from subject features. Used for exploring the relationship between healthy …
machine learning from subject features. Used for exploring the relationship between healthy …