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AI-driven innovations in Alzheimer's disease: Integrating early diagnosis, personalized treatment, and prognostic modelling
Alzheimer's disease (AD) presents a significant challenge in neurodegenerative research
and clinical practice due to its complex etiology and progressive nature. The integration of …
and clinical practice due to its complex etiology and progressive nature. The integration of …
Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review
Introduction Artificial intelligence (AI) and neuroimaging offer new opportunities for
diagnosis and prognosis of dementia. Methods We systematically reviewed studies …
diagnosis and prognosis of dementia. Methods We systematically reviewed studies …
Artificial intelligence for dementia prevention
INTRODUCTION A wide range of modifiable risk factors for dementia have been identified.
Considerable debate remains about these risk factors, possible interactions between them …
Considerable debate remains about these risk factors, possible interactions between them …
Artificial intelligence for neurodegenerative experimental models
INTRODUCTION Experimental models are essential tools in neurodegenerative disease
research. However, the translation of insights and drugs discovered in model systems has …
research. However, the translation of insights and drugs discovered in model systems has …
Biomarkers for cognitive impairment in alpha-synucleinopathies: an overview of systematic reviews and meta-analyses
Cognitive impairment (CI) is common in α-synucleinopathies, ie, Parkinson's disease, Lewy
bodies dementia, and multiple system atrophy. We summarize data from systematic …
bodies dementia, and multiple system atrophy. We summarize data from systematic …
Integrating demographics and imaging features for various stages of dementia classification: Feed forward neural network multi-class approach
Background: MRI magnetization-prepared rapid acquisition (MPRAGE) is an easily
available imaging modality for dementia diagnosis. Previous studies suggested that …
available imaging modality for dementia diagnosis. Previous studies suggested that …
A novel approach to dementia prediction of DTI markers using BALI, LIBRA, and machine learning techniques
Early prediction of dementia and disease progression remains challenging. This study
presents a novel machine learning framework for dementia diagnosis by integrating …
presents a novel machine learning framework for dementia diagnosis by integrating …
Medical technologies, telemedicine and artificial intelligence for neurotrauma and neurorehabilitation
Traumatic brain injury (TBI) is the most common neurological condition, with an estimated
incidence of 500–1000 cases per 100 000 people per year and a substantial public health …
incidence of 500–1000 cases per 100 000 people per year and a substantial public health …
[HTML][HTML] Advancing Alzheimer's Therapy: Computational Strategies and Treatment Innovations
Alzheimer's disease (AD) is a multifaceted neurodegenerative condition distinguished by the
occurrence of memory impairment, cognitive deterioration, and neuronal impairment …
occurrence of memory impairment, cognitive deterioration, and neuronal impairment …
A novel approach to dementia prediction leveraging recursive feature elimination and decision tree
A Akbarifar, A Maghsoudpour, F Mohammadian… - 2024 - researchsquare.com
Early prediction of dementia and disease progression remains challenging. This study
presents a novel machine learning framework for dementia diagnosis by integrating …
presents a novel machine learning framework for dementia diagnosis by integrating …