首页|Beijing Hospital Reports Findings in Atrial Fibrillation (Machine learning-based identification and validation of aging-related genes in cardiomyocytes from pat ients with atrial fibrillation)
Beijing Hospital Reports Findings in Atrial Fibrillation (Machine learning-based identification and validation of aging-related genes in cardiomyocytes from pat ients with atrial fibrillation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Heart Disorders and Di seases - Atrial Fibrillation is the subject of a report. According to news repor ting originating from Beijing, People’s Republic of China, by NewsRx corresponde nts, research stated, “Aging is a key risk factor for atrial fibrillation (AF), a prevalent cardiac disorder among the elderly. This study aims to elucidate the genetic underpinnings of AF in the context of aging.” Our news editors obtained a quote from the research from Beijing Hospital, “We a nalyzed 12,403 genes from the GSE2240 database and 279 age-related genes from th e CellAge database. Machine learning algorithms, including support vector machin es and random forests, were employed to identify genes significantly associated with AF. Among the genes studied, 76 were found to be potential candidates in th e development of AF. Notably, four genes - PTTG1, AR, RAD21, and YAP1 - stood ou t with a Receiver Operating Characteristic Area Under the Curve (ROC AUC) of 0.9 , signifying high predictive power. Logistic regression, validated through 10-fo ld cross-validation and Bootstrap resampling, was determined as the most suitabl e model for internal validation. The discovery of these four genes could improve diagnostic accuracy for AF in the aged population.”
BeijingPeople’s Republic of ChinaAsi aAtrial FibrillationCardiac ArrhythmiasCardiologyCardiomyocyteCyborgsEmerging TechnologiesGeneticsHealth and MedicineHeart DiseaseHeart Diso rders and DiseasesMachine LearningRisk and Prevention
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