Thyroid disrupting chemicals

V Calsolaro, G Pasqualetti, F Niccolai… - International journal of …, 2017 - mdpi.com
Endocrine disruptor compounds are exogenous agents able to interfere with a gland
function, exerting their action across different functional passages, from the synthesis to the …

Dementia risk and prevention by targeting modifiable vascular risk factors

S Tariq, PA Barber - Journal of neurochemistry, 2018 - Wiley Online Library
The incidence of dementia is expected to double in the next 20 years and will contribute to
heavy social and economic burden. Dementia is caused by neuronal loss that leads to brain …

Brain MRI analysis for Alzheimer's disease diagnosis using CNN-based feature extraction and machine learning

D AlSaeed, SF Omar - Sensors, 2022 - mdpi.com
Alzheimer's disease is the most common form of dementia and the fifth-leading cause of
death among people over the age of 65. In addition, based on official records, cases of …

Healthy brain aging and delayed dementia in Texas rural elderly

T Basu, U Sehar, K Malhotra, J Culberson… - Ageing Research …, 2023 - Elsevier
Healthy aging is the process of preserving and enhancing one's independence, physical
and mental well-being, and overall quality of life. It involves the mental, emotional, and …

[HTML][HTML] A comparison of resting state EEG and structural MRI for classifying Alzheimer's disease and mild cognitive impairment

FR Farina, DD Emek-Savaş, L Rueda-Delgado… - Neuroimage, 2020 - Elsevier
Alzheimer's disease (AD) is the leading cause of dementia, accounting for 70% of cases
worldwide. By 2050, dementia prevalence will have tripled, with most new cases occurring …

[HTML][HTML] Deep learning-based EEG analysis to classify normal, mild cognitive impairment, and dementia: Algorithms and dataset

M Kim, YC Youn, J Paik - NeuroImage, 2023 - Elsevier
For automatic EEG diagnosis, this paper presents a new EEG data set with well-organized
clinical annotations called Chung-Ang University Hospital EEG (CAUEEG), which has event …

[HTML][HTML] Discrimination and conversion prediction of mild cognitive impairment using convolutional neural networks

C Wu, S Guo, Y Hong, B **ao, Y Wu… - … imaging in medicine …, 2018 - ncbi.nlm.nih.gov
Background Recently, studies have demonstrated that machine learning techniques,
particularly cutting-edge deep learning technology, have achieved significant progression …

The value of neuroimaging in dementia diagnosis

CA Raji, TLS Benzinger - CONTINUUM: Lifelong Learning in …, 2022 - journals.lww.com
The Value of Neuroimaging in Dementia Diagnosis : CONTINUUM: Lifelong Learning in
Neurology Account Register Activate Subscription Help Subscribe American Academy of …

Longitudinal changes in surface based brain morphometry measures in amnestic mild cognitive impairment and Alzheimer's Disease

T Bachmann, ML Schroeter, K Chen, EM Reiman… - NeuroImage: Clinical, 2023 - Elsevier
Background Alzheimer's disease (AD) is associated with marked brain atrophy. While
commonly used structural MRI imaging methods do not account for the complexity of human …

MRI-based evaluation of structural degeneration in the ageing brain: Pathophysiology and assessment

LA Grajauskas, W Siu, G Medvedev, H Guo… - Ageing research …, 2019 - Elsevier
Advances in MRI technology have significantly contributed to our ability to understand the
process of brain ageing, allowing us to track and assess changes that occur during normal …