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Principal Investigator  
Principal Investigator's Name: ferial abuhantash
Institution: Khalifa University
Department: Biomedical Engineering
Proposed Analysis: Alzheimer's disease (A.D.) is an insidious, progressive, and degenerative neurodegenerative disease that destroys normal brain functionality. It targets the elderly, although it is not part of the normal aging process. The disease begins 20 years or more before its early symptoms appear. The symptoms start with memory loss and language problems that progress over time to losing the ability to carry on normal daily activities. At the later stage, the patient becomes bed-bound, requires around-the-clock care, and dies due to respiratory syndrome. Unfortunately, to date, A.D. onset and progression etiology has not been identified, explaining the high failure rate of dementia therapies (accounts by 99.6%). Dementia cases are expected to increase in the low and middle-income countries, unlike the western countries, due to the management strategy for some dementia risk factors such as cardiovascular disease, hypertension, and diabetes. A.D. has a physical, emotional, financial, and economic burden on the patient as well as on society, families, and caregivers. Alzheimer's Association reported an approximate 5.7 million Americans diagnosed with A.D. in 2018, and the number expected to double by 2050 which made A.D. the sixth leading cause of deaths among Americans. On the bright side, up to 40% of dementia can be delayed or prevented by avoiding its risk factors and diagnosing it in its early stages. For this reason, this study will focus on the use of machine learning and artificial intelligence to analyze heterogeneous dementia patients' datasets for predicting dementia in its early stages and identifying its risk factors.
Additional Investigators