When does Alzheimer′ s disease really start? The role of biomarkers
A Lloret, D Esteve, MA Lloret, A Cervera-Ferri… - International journal of …, 2019 - mdpi.com
While Alzheimer's disease (AD) classical diagnostic criteria rely on clinical data from a
stablished symptomatic disease, newer criteria aim to identify the disease in its earlier …
stablished symptomatic disease, newer criteria aim to identify the disease in its earlier …
Trustworthy artificial intelligence in Alzheimer's disease: state of the art, opportunities, and challenges
Abstract Medical applications of Artificial Intelligence (AI) have consistently shown
remarkable performance in providing medical professionals and patients with support for …
remarkable performance in providing medical professionals and patients with support for …
A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease
Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and
progression detection have been intensively studied. Nevertheless, research studies often …
progression detection have been intensively studied. Nevertheless, research studies often …
Multimodal multitask deep learning model for Alzheimer's disease progression detection based on time series data
Early prediction of Alzheimer's disease (AD) is crucial for delaying its progression. As a
chronic disease, ignoring the temporal dimension of AD data affects the performance of a …
chronic disease, ignoring the temporal dimension of AD data affects the performance of a …
Robust hybrid deep learning models for Alzheimer's progression detection
The prevalence of Alzheimer's disease (AD) in the growing elderly population makes
accurately predicting AD progression crucial. Due to AD's complex etiology and …
accurately predicting AD progression crucial. Due to AD's complex etiology and …
Dementia detection from speech using machine learning and deep learning architectures
Dementia affects the patient's memory and leads to language impairment. Research has
demonstrated that speech and language deterioration is often a clear indication of dementia …
demonstrated that speech and language deterioration is often a clear indication of dementia …
Improved Alzheimer's disease detection by MRI using multimodal machine learning algorithms
Adult-onset dementia disorders represent a challenge for modern medicine. Alzheimer's
disease (AD) represents the most diffused form of adult-onset dementias. For half a century …
disease (AD) represents the most diffused form of adult-onset dementias. For half a century …
A practical computerized decision support system for predicting the severity of Alzheimer's disease of an individual
Computerized clinical decision support systems can help to provide objective, standardized,
and timely dementia diagnosis. However, current computerized systems are mainly based …
and timely dementia diagnosis. However, current computerized systems are mainly based …
Association of the use of hearing aids with the conversion from mild cognitive impairment to dementia and progression of dementia: a longitudinal retrospective study
M Bucholc, PL McClean, S Bauermeister… - … Research & Clinical …, 2021 - Wiley Online Library
Introduction Hearing aid usage has been linked to improvements in cognition,
communication, and socialization, but the extent to which it can affect the incidence and …
communication, and socialization, but the extent to which it can affect the incidence and …
Practical strategies for extreme missing data imputation in dementia diagnosis
N McCombe, S Liu, X Ding, G Prasad… - IEEE journal of …, 2021 - ieeexplore.ieee.org
Accurate computational models for clinical decision support systems require clean and
reliable data but, in clinical practice, data are often incomplete. Hence, missing data could …
reliable data but, in clinical practice, data are often incomplete. Hence, missing data could …