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Active Investigations

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: Harvey Felipe
Institution: Ateneo de Manila University
Department: Mathematics Department
Country:
Proposed Analysis: Good day! I am Harvey Felipe, an undergraduate BS Applied Mathematics-Master in Data Science student representing our team under the Collab Analytics Research Group of the Department of Mathematics in the Ateneo de Manila University in the Philippines. We are requesting access to ADNI's available Alzheimers' Disease datasets for the purposes of our undergraduate thesis that aims to use machine learning and deep learning techniques to analyze genetic markers that identify which are most predictive of leading to the development of the disease so that proper proactive measures are made for the most at-risk patients even before symptoms appear. We are requesting to use your provided datasets so that we may be able to use them as reference to train our models. As such, it would be of great help to us if ADNI would allow us access to the datasets. Thank you for your time, and we hope this finds you well!
Additional Investigators  
Investigator's Name: Angela Nicole Isabel Ferrer
Proposed Analysis: We are requesting access to ADNI's Alzheimer's Disease datasets for the purposes of our undergraduate thesis that aims to use machine learning, deep learning, and natural language processing techniques on genetic data of Alzheimer's patients to identify genetic markers that are most predictive of the development of Alzheimer's disease.
Investigator's Name: Ronith Agnes Vicente
Proposed Analysis: We are requesting access to ADNI's Alzheimer's Disease datasets for the purposes of our undergraduate thesis that aims to use machine learning, deep learning, and natural language processing techniques on genetic data of Alzheimer's patients to identify genetic markers that are most predictive of the development of Alzheimer's disease.