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Numerous drugs (including disease-modifying therapies, cognitive enhancers and neuropsychiatric treatments) are being developed for Alzheimer's and related dementias (ADRD). Emerging neuroimaging modalities, and genetic and other biomarkers potentially enhance diagnostic and prognostic accuracy. These advances need to be assessed in real-world studies (RWS).

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Up to date, there are no precise reports of the prevalence of dementia with Lewy bodies (DLB) in Latin America. This can be explained by the lack of research studies and general little awareness about the disease. Notably, collaborative clinical studies are lacking, and DLB patients remain underrepresented despite their significant morbidity.

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Background: This study explores Alzheimer's prediction through brain MRI images, utilizing Convolutional Neural Networks (CNNs) and Lime interpretability. Based on an extensive ADNI MRI dataset, we demonstrate promising results in predicting Alzheimer's disease. Local Interpretable Model Agnostic Explanations (LIME) shed light on decision-making processes, enhancing transparency.

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