This comprehensive review examines the integration of Quantitative Electroencephalography (qEEG) and Artificial Intelligence (AI) in the detection and diagnosis of Alzheimer's Disease (AD). Through systematic analysis of 11 key studies across multipl...
Alzheimer's Disease (AD) and related dementias are significant global health issues characterized by progressive cognitive decline and memory loss. Computer-aided systems can help physicians in the early and accurate detection of AD, enabling timely ...
Traditional fluorescence lifetime imaging (FLIM) provides valuable quantitative insights for biomedical and molecular biology research, but often relies on computationally intensive datafitting methods to extract meaningful metrics. To address this l...
Liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in untargeted metabolomics. However, the diverse chemical and physical properties of metabolites often require the use of several different analytical assays for ...
The progression of Alzheimer's disease is relentless, leading to a worsening of mental faculties over time. Currently, there is no remedy for this illness. Accurate detection and prompt intervention are pivotal in mitigating the progression of the di...
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leading to cognitive and behavioral decline. With the aging global population, AD incidence and its socioeconomic burden are increasing. Developing effectiv...
BACKGROUND: The complex pathogenesis of Alzheimer's disease (AD) has resulted in limited current biomarkers for its classification and diagnosis, necessitating further investigation into reliable universal biomarkers or combinations.
Alzheimer's disease (AD) constitutes a neurodegenerative disorder predominantly observed in the geriatric population. If AD can be diagnosed early, both in terms of prevention and treatment, it is very beneficial to patients. Therefore, our team prop...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that significantly impacts cognitive function, posing a major global health challenge. Despite its rising prevalence, particularly in low and middle-income countries, early diagnosi...
Traditional diagnostic methods for Alzheimer's disease often suffer from low accuracy and lengthy processing times, delaying crucial interventions and patient care. Deep convolutional neural networks trained on MRI data can enhance diagnostic precisi...
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