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Tobacco use remains the leading preventable cause of cancer mortality worldwide, with marked disparities in cancer incidence and outcomes across racial and ethnic groups. This study investigates the genetic determinants of tobacco carcinogen metabolism among smokers, focusing on ancestry-informative markers (AIMs) near genes involved in metabolic activation (Phase I), detoxification (Phase II), and transport (Phase III) of tob...
Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegenerationNARA Subscribed
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can fi...