Extensive review on the role of machine learning for multifactorial genetic disorders prediction
The culture of employing machine learning driven assistance and decision making is
currently adopted by a variety of industries. Artificial intelligence encompasses a wide range …
currently adopted by a variety of industries. Artificial intelligence encompasses a wide range …
Biomarkers for Alzheimer's disease in the current state: a narrative review
S Gunes, Y Aizawa, T Sugashi, M Sugimoto… - International journal of …, 2022 - mdpi.com
Alzheimer's disease (AD) has become a problem, owing to its high prevalence in an aging
society with no treatment available after onset. However, early diagnosis is essential for …
society with no treatment available after onset. However, early diagnosis is essential for …
Artificial intelligence models in the diagnosis of adult-onset dementia disorders: A review
Background: The progressive aging of populations, primarily in the industrialized western
world, is accompanied by the increased incidence of several non-transmittable diseases …
world, is accompanied by the increased incidence of several non-transmittable diseases …
[HTML][HTML] Disease progression modelling of Alzheimer's disease using probabilistic principal components analysis
The recent biological redefinition of Alzheimer's Disease (AD) has spurred the development
of statistical models that relate changes in biomarkers with neurodegeneration and …
of statistical models that relate changes in biomarkers with neurodegeneration and …
Machine learning, artificial intelligence and the prediction of dementia
A Merkin, R Krishnamurthi… - Current opinion in …, 2022 - journals.lww.com
Application of machine learning technologies in detection and prediction of dementia may
provide an advantage to psychiatry and neurology by promoting a better understanding of …
provide an advantage to psychiatry and neurology by promoting a better understanding of …
Advances in blood biomarkers for Alzheimer disease (AD): A review
Alzheimer disease (AD) and Alzheimer Disease and Related Dementias (AD/ADRD) are
growing public health challenges globally affecting millions of older adults, necessitating …
growing public health challenges globally affecting millions of older adults, necessitating …
[Retracted] Implementing Critical Machine Learning (ML) Approaches for Generating Robust Discriminative Neuroimaging Representations Using Structural Equation …
Critical ML or CML is a critical approach development of the standard ML (SML) procedure.
Conventional ML (ML) is being used in radiology departments where complex neuroimages …
Conventional ML (ML) is being used in radiology departments where complex neuroimages …
[HTML][HTML] A hierarchical attention-based multimodal fusion framework for predicting the progression of Alzheimer's disease
Early detection and treatment can slow the progression of Alzheimer's Disease (AD), one of
the most common neurodegenerative diseases. Recent studies have demonstrated the …
the most common neurodegenerative diseases. Recent studies have demonstrated the …
[HTML][HTML] A novel integrated logistic regression model enhanced with recursive feature elimination and explainable artificial intelligence for dementia prediction
Dementia is a major global health issue that significantly impacts millions of individuals,
families, and societies worldwide, creating a substantial burden on healthcare systems. This …
families, and societies worldwide, creating a substantial burden on healthcare systems. This …
Dementia prediction in the general population using clinically accessible variables: a proof-of-concept study using machine learning. The AGES-Reykjavik study
EL Twait, CL Andaur Navarro, V Gudnason… - BMC medical informatics …, 2023 - Springer
Background Early identification of dementia is crucial for prompt intervention for high-risk
individuals in the general population. External validation studies on prognostic models for …
individuals in the general population. External validation studies on prognostic models for …