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Communication Dans Un Congrès Année : 2017

Predictive Modeling of the Severity/Progression of Alzheimer's Diseases

Résumé

Alzheimer's disease (AD) cannot be cured or slowed down with today's medication. Scientific studies have found that 1) the progression of AD is highly correlated to a cognition decline, 2) cognition drop is a precursor of Alzheimer's disease, and 3) making lifestyle changes and training the brain can slow down AD progression. This project aims to develop a predictive model to know the progression of an AD patient. Factors that influence the disease's severity and progression are determined, which would help facilitate developing a set of personalized care instructions to guide individuals in making the necessary lifestyle choices to retain or rejuvenate their brain's cognitive ability. Ultimately, the developed model can be potentially incorporated into a convenient self-diagnostic tool for the public to use at home.
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Dates et versions

hal-01577958 , version 1 (28-08-2017)

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Copyright (Tous droits réservés)

Identifiants

  • HAL Id : hal-01577958 , version 1

Citer

Robin G Qiu, Jason L Qiu, Youakim Badr. Predictive Modeling of the Severity/Progression of Alzheimer's Diseases. IEEE International Conference on Grey Systems and Intelligent Services, Aug 2017, Stockholm, Sweden. pp.400-403. ⟨hal-01577958⟩
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