Publications by authors named "Buhari Ibrahim"

This review aimed to evaluate and synthesize information on the effects of first-aid education in road traffic crashes on knowledge, attitudes, and skills among non-healthcare professionals. A qualitative study was designed according to the Prepared Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards to evaluate three outcomes, knowledge, skills, and attitude. The search strategy was performed in five databases (Science Direct, Scopus, CINAHL Plus, PubMed, and Google Scholar) to retrieve primary studies published between January 2011 and December 2021.

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Background: Alzheimer's disease (AD) is a major neurocognitive disorder identified by memory loss and a significant cognitive decline based on previous level of performance in one or more cognitive domains that interferes in the independence of everyday activities. The accuracy of imaging helps to identify the neuropathological features that differentiate AD from its common precursor, mild cognitive impairment (MCI). Identification of early signs will aid in risk stratification of disease and ensures proper management is instituted to reduce the morbidity and mortality associated with AD.

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Article Synopsis
  • Resting-state fMRI (rs-fMRI) identifies functional connectivity abnormalities in the brains of Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients, particularly in the default mode network (DMN).
  • A systematic review was conducted to assess the diagnostic effectiveness of rs-fMRI for detecting these abnormalities using machine learning methods, notably the support vector machine (SVM) algorithm and various multimodal features.
  • Key findings reveal that the posterior cingulate cortex (PCC) is heavily impacted in AD patients, while MCI patients show reduced connectivity between the PCC and anterior cingulate cortex (ACC), but challenges like data variability and algorithm discrepancies hinder the broader application of machine learning for diagnosing and predicting AD.
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Functional magnetic resonance imaging (fMRI) is a non-invasive imaging modality that enables the assessment of neural connectivity and oxygen utility of the brain using blood oxygen level dependent (BOLD) imaging sequence. Electroencephalography (EEG), on the other hands, looks at cortical electrical impulses of the brain thus detecting brainwave patterns during rest and thought processing. The combination of these two modalities is called fMRI with simultaneous EEG (fMRI-EEG), which has emerged as a new tool for experimental neuroscience assessments and has been applied clinically in many settings, most commonly in epilepsy cases.

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