The journals of gerontology. Series B, Psychological sciences and social sciences
Mar 12, 2025
OBJECTIVES: This study aimed to explore a broad range of predictors of generativity in older adults. The study included over 60 predictors across multiple domains, including personality, daily functioning, socioeconomic factors, health status, and me...
The association between chronic lung diseases (CLDs) and the risk of cardiovascular diseases (CVDs) has been extensively recognized. Nevertheless, conventional approaches for CVD risk evaluation cannot fully capture the risk factors (RFs) related to ...
Septic acute respiratory distress syndrome (ARDS) is a complex and noteworthy type, but its molecular mechanism has not been fully elucidated. The aim is to explore specific biomarkers to diagnose sepsis-induced ARDS. Gene expression data of sepsis a...
The integration of big data analytics and machine learning (ML) into hematology has ushered in a new era of precision medicine, offering transformative insights into disease management. By leveraging vast and diverse datasets, including genomic profi...
BACKGROUND: The global prevalence of non-alcoholic steatohepatitis (NASH) and its associated risk of adverse outcomes, particularly in patients with advanced liver fibrosis, underscores the importance of early and accurate diagnosis.
BACKGROUND AND AIMS: The importance of risk stratification in patients with chest pain extends beyond diagnosis and immediate treatment. This study sought to evaluate the prognostic value of electrocardiogram feature-based machine learning models to ...
The accurate categorization of compounds within the anatomical therapeutic chemical (ATC) system is fundamental for drug development and fundamental research. Although this area has garnered significant research focus for over a decade, the majority ...
Nitrogen-fixing microorganisms play a critical role in the global nitrogen cycle by converting atmospheric nitrogen into ammonia through the action of nitrogenase (EC 1.18.6.1). In this study, we employed six machine learning algorithms to model the ...
Integrating and analyzing multiple omics datasets, such as genomics, environmental influences, and imaging endophenotypes, has yielded an abundance of candidate biomarkers. However, translating such findings into beneficial clinical knowledge for dis...
Multi-omics data often suffer from the "big $p$, small $n$" problem where the dimensionality of features is significantly larger than the sample size, making the integration of multi-omics data for survival analysis of a specific cancer particularly ...
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