A review in the International Journal of Medical Engineering and Informatics has surveyed current early detection methods for Alzheimer's disease, a prevalent neurodegenerative condition affecting millions of people worldwide.
has surveyed current early detection methods for Alzheimer's disease, a prevalent neurodegenerative condition affecting millions of people worldwide.
The work looks into the progression, causes, and diagnosis of Alzheimer's and emphasizes that a multi-modal approach coupled with advanced machine learning techniques could lead to much earlier diagnosis for many patients. Early diagnosis offers better options for planning and ongoing care. As theAlzheimer's disease is a neurodegenerative disorder characterized by cognitive impairment and memory loss.
There is no cure for this debilitating and ultimately lethal condition but the importance of detecting it in its early stages cannot be overstated given the devastating impact it has on the patient and those caring for them. Early diagnosis not only allows individuals to communicate their needs to loved ones but also empowers them to make crucial decisions regarding finances and legal matters that will come into play as the disease progresses.
While a definitive scientific diagnosis is really only possible post mortem, a combination of observations of behavior as well as
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