Alzheimer's disease (AD) biomarkers (Aβ42 or Tau 181) have high diagnostic performance. However, when they are altered, it indicates that irreversible pathology has developed in the brain. Therefore, there is a lack of early prediction or monitoring ...
Early diagnosis of Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI), is critical for effective prevention and treatment. Computer-aided diagnosis using magnetic resonance imaging (MRI) provides a cost-effective and objectiv...
Pholiota adiposa is recognized for its health benefits, particularly in Alzheimer's disease (AD), but its molecular mechanism remains elusive. Our study employs network pharmacology and machine learning to uncover its therapeutic potential. We constr...
Alzheimer's disease is a progressive neurological disorder that profoundly affects cognitive functions and daily activities. Rapid and precise identification is essential for effective intervention and improved patient outcomes. This research introdu...
Alzheimer's Disease (AD) is neurodegenerative disorder that causes cognitive decline, memory loss, confusion, and changes in behavior. Early and accurate detection is important for timely intervention, current diagnostic methods can be slow, expensiv...
Alzheimer's disease (AD), a progressive neurodegenerative disorder, significantly impacts patient survival, prompting the need for accurate prognostic tools. Lifestyle factors and physical activity levels have been identified as critical modifiable r...
BACKGROUND: Biomedical research requires large, diverse samples to produce unbiased results. Retrospective data harmonization is often used to integrate existing datasets to create these samples, but the process is labor-intensive. Automated methods ...
Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions worldwide. In the absence of effective treatment options, early diagnosis is crucial for initiating management strategies to delay disease onset and slow down its progress...
Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest Europe...
BACKGROUND: Individualized prediction of health outcomes supports clinical medicine and decision making. Our primary objective was to offer a comprehensive survey of methods for the dynamic prediction of Alzheimer's disease (AD), encompassing both co...
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