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Related Concept Videos

Dementia01:30

Dementia

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Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
The progression of dementia is generally gradual....
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Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
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Alzheimer's Disease (AD), a neurodegenerative disorder, is pathologically identified by amyloid plaques and neurofibrillary tangles composed of tau protein. AD pharmacotherapy aims to manage cognitive symptoms, delay disease progression, and treat behavioral symptoms. The treatment is primarily symptomatic and palliative, with no definitive disease-modifying therapy available. Cholinesterase inhibitors, including donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne), are...
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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
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Neurodegenerative disorders are progressive diseases that cause irreversible damage and loss to neurons in specific brain areas. Examples of these disorders include Parkinson's disease, Alzheimer's disease, Multiple Sclerosis (MS), and Amyotrophic Lateral Sclerosis (ALS). These disorders share characteristics such as proteinopathies, selective neuronal vulnerability, and a complex interplay between genetic and environmental factors. The primary therapeutic goal for these conditions is...
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Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
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Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
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Personalized Multi-Domain Digital Platform for Dementia Prevention.

Seyed-Mohammad Fereshtehnejad1,2, Karim Keshavjee2, Abbas Zavar2

  • 1Faculty of Medicine, University of Toronto, Toronto, ON, Canada.

Studies in Health Technology and Informatics
|February 19, 2025
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This initiative uses a digital platform to create personalized dementia prevention plans. It analyzes health and lifestyle data to offer tailored, evidence-based recommendations for reducing dementia risk.

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Area of Science:

  • Neuroscience and Public Health
  • Digital Health and AI in Medicine

Background:

  • Dementia poses a significant global health burden.
  • Current dementia prevention strategies often lack personalization.
  • Integrating multi-domain risk factor data is crucial for effective prevention.

Purpose of the Study:

  • To introduce the Personalized Multi-Domain Digital Platform for Dementia Prevention (PM(DP)*2).
  • To outline an evidence-based approach for tailored dementia risk reduction.
  • To leverage technology for dynamic and personalized prevention strategies.

Main Methods:

  • Collection and analysis of multidimensional data on modifiable dementia risk factors (lifestyle, cardiovascular, environmental).
  • Development of individualized dementia risk profiles.
  • Utilization of machine learning and generative AI for personalized recommendations.

Main Results:

  • Conceptualization of a platform generating individualized risk profiles.
  • Design of a system for tailored, evidence-driven prevention strategies.
  • Enhanced recommendation capabilities through AI and machine learning.

Conclusions:

  • The PM(DP)*2 platform offers a novel, technology-driven approach to dementia prevention.
  • Personalized interventions based on multi-domain data can effectively reduce dementia burden.
  • AI and machine learning are key to delivering dynamic and evidence-based dementia prevention.