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Background: Current tools for Alzheimer's disease screening and staging used in clinical research (e.g. ACE-3, ADAS-Cog) require substantial face-to-face time with trained professionals, and may be affected by subjectivity, "white coat syndrome" and other biases.
View Article and Find Full Text PDFBackground: The perirhinal cortex is vulnerable to early phosphorylated tau (p-tau) accumulation; deterioration of this region in the prodromal stages of Alzheimer's Disease (AD) is associated with impaired 'complex' perceptual discrimination. This research examined whether there is a disadvantageous gene-dose effect of Apolipoprotein (APOE) e4 on perceptual discrimination in mid-life, facilitating greater understanding of how and when the deleterious effects of this variant emerge.
Methods: Three-hundred and thirteen mid-aged adults (45-65 years; 51% female; recruited by NIHR BioResource) completed a Greebles 'odd-one-out' task.
Technology and Dementia Preconference.
Alzheimers Dement
December 2024
Cumulus Neuroscience, Dublin, Ireland.
Background: Current tools for Alzheimer's disease screening and staging used in clinical research (e.g. ACE-3, ADAS-Cog) require substantial face-to-face time with trained professionals, and may be affected by subjectivity, "white coat syndrome" and other biases.
View Article and Find Full Text PDFThe association between the body roundness index and the risk of chronic kidney disease in US adults.
Front Med (Lausanne)
December 2024
Department of Cardiology, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, Sichuan, China.
Aim: We aimed to systematically assess whether the level of body roundness index (BRI) is associated with the risk of developing chronic kidney disease (CKD) in US adults.
Methods: The studied data was extracted from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. A total of 29,062 participants aged ≥20 years with complete information about BRI and CKD were included in this study.
EEG channel and feature investigation in binary and multiple motor imagery task predictions.
Front Hum Neurosci
December 2024
Department of Biomedical Engineering, Izmir Katip Celebi University, Izmir, Türkiye.
Introduction: Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult to achieve high classification accuracy. Although various machine learning methods have already proven useful to that effect, the use of many features and ineffective EEG channels often leads to a complex structure of classifier algorithms.
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