[HTML][HTML] Machine learning for dementia prediction: a systematic review and future research directions
Abstract Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully
provided automated solutions to numerous real-world problems. Healthcare is one of the …
provided automated solutions to numerous real-world problems. Healthcare is one of the …
[HTML][HTML] Applications of artificial intelligence in the neuropsychological assessment of dementia: A systematic review
I Veneziani, A Marra, C Formica, A Grimaldi… - Journal of Personalized …, 2024 - mdpi.com
In the context of advancing healthcare, the diagnosis and treatment of cognitive disorders,
particularly Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD), pose significant …
particularly Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD), pose significant …
[HTML][HTML] Classification of Alzheimer's disease and frontotemporal dementia using routine clinical and cognitive measures across multicentric underrepresented …
MA Maito, H Santamaría-García… - The Lancet Regional …, 2023 - thelancet.com
Background Global brain health initiatives call for improving methods for the diagnosis of
Alzheimer's disease (AD) and frontotemporal dementia (FTD) in underrepresented …
Alzheimer's disease (AD) and frontotemporal dementia (FTD) in underrepresented …
Development of criteria for cognitive dysfunction in post-COVID syndrome: the IC-CoDi-COVID approach
Background We aimed to develop objective criteria for cognitive dysfunction associated with
the post-COVID syndrome. Methods Four hundred and four patients with post-COVID …
the post-COVID syndrome. Methods Four hundred and four patients with post-COVID …
[HTML][HTML] An intelligent learning system for unbiased prediction of dementia based on autoencoder and adaboost ensemble learning
Dementia is a neurological condition that primarily affects older adults and there is still no
cure or therapy available to cure it. The symptoms of dementia can appear as early as 10 …
cure or therapy available to cure it. The symptoms of dementia can appear as early as 10 …
Wearable sensors and features for diagnosis of neurodegenerative diseases: A systematic review
Objective Neurodegenerative diseases affect millions of families around the world, while
various wearable sensors and corresponding data analysis can be of great support for …
various wearable sensors and corresponding data analysis can be of great support for …
[HTML][HTML] GA-MADRID: Design and validation of a machine learning tool for the diagnosis of Alzheimer's disease and frontotemporal dementia using genetic algorithms
F García-Gutierrez, J Díaz-Álvarez… - Medical & Biological …, 2022 - Springer
Artificial Intelligence aids early diagnosis and development of new treatments, which is key
to slow down the progress of the diseases, which to date have no cure. The patients' …
to slow down the progress of the diseases, which to date have no cure. The patients' …
[HTML][HTML] Early prediction of dementia using feature extraction battery (feb) and optimized support vector machine (svm) for classification
Dementia is a cognitive disorder that mainly targets older adults. At present, dementia has
no cure or prevention available. Scientists found that dementia symptoms might emerge as …
no cure or prevention available. Scientists found that dementia symptoms might emerge as …
Forecasting soybean oil extraction using cyclopentyl methyl ether through soft computing models with a density functional theory study
This work presents a thermo-statistical assessment using soft computing models to describe
green soybean oil extraction by cyclopentyl methyl ether (CPME). Experimental data were …
green soybean oil extraction by cyclopentyl methyl ether (CPME). Experimental data were …
Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
INTRODUCTION Verbal fluency tasks are common in Alzheimer's disease (AD)
assessments. Yet, standard valid response counts fail to reveal disease‐specific semantic …
assessments. Yet, standard valid response counts fail to reveal disease‐specific semantic …