There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Tayaba Abbasi |
| Institution: | Khalifa University |
| Department: | Biomedical Engineering |
| Country: | |
| Proposed Analysis: | Dementia is an insidious, progressive, and degenerative neurodegenerative disease that destroys normal brain functionality. It targets the elderly, although it is not part of the usual 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 and requires around-the-clock care. According to the World Health Organization (WHO), approximately 50 million people worldwide are diagnosed with dementia, with nearly 10 million new cases annually. The most common form of dementia is Alzheimer's disease, which contributes to 60–70% of all cases. Other major forms are vascular dementia and dementia with Lewy bodies. Alzheimer can be delayed or prevented by avoiding its risk factors and diagnosing it in its early stage. For this reason, this study will focus on the use of machine learning, artificial intelligence, and causal inference models to analyze dementia patients' dataset for predicting dementia in its early stages and identifying its risk factors. The study will aim to build an early-stage predictive model, identify new (un-reported) dementia risk factors, and stratify patients based on the variation of the risk factors to help manage and reduce the prevalence and complication of dementia. |
| Additional Investigators | |
| Investigator's Name: | Dr Aamna Al Shehhi |
| Proposed Analysis: | Dementia is an insidious, progressive, and degenerative neurodegenerative disease that destroys normal brain functionality. It targets the elderly, although it is not part of the usual 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 and requires around-the-clock care. According to the World Health Organization (WHO), approximately 50 million people worldwide are diagnosed with dementia, with nearly 10 million new cases annually. The most common form of dementia is Alzheimer's disease, which contributes to 60–70% of all cases. Other major forms are vascular dementia and dementia with Lewy bodies. Alzheimer can be delayed or prevented by avoiding its risk factors and diagnosing it in its early stage. For this reason, this study will focus on the use of machine learning, artificial intelligence, and causal inference models to analyze dementia patients' dataset for predicting dementia in its early stages and identifying its risk factors. The study will aim to build an early-stage predictive model, identify new (un-reported) dementia risk factors, and stratify patients based on the variation of the risk factors to help manage and reduce the prevalence and complication of dementia. |
