Ongoing Investigations

ADNI data is made available to researchers around the world. As such, there are many active research projects accessing and applying the shared ADNI data. To further encourage Alzheimer’s disease research collaboration, and to help prevent duplicate efforts, the list below shows the specific research focus of the active ADNI investigations. This information is requested annually as a requirement for data access.

Principal Investigator  
Principal Investigator's Name: Haifa Alshehri
Institution: Taif University
Department: Computer Science
Country:
Proposed Analysis: Our goal in the research is a review on the various invasive and non-invasive biomarkers related to AD patients and the classification techniques used in the early diagnosis of Alzheimer’s disease. It highlights the factors that affect early AD detection. It concludes that further research on bio-markers is necessary for early AD detection. Optimization of classification techniques can help improve the classification accuracy to some extent. Combining the features obtained from different neuro-images including functional and structural MRI and PET images and other biomarkers can help to improve the prediction rate of MCI from normal patients.
Additional Investigators  
Investigator's Name: Samsad Beagum
Proposed Analysis: Our goal in the research is a review on the various invasive and non-invasive biomarkers related to AD patients and the classification techniques used in the early diagnosis of Alzheimer’s disease. It highlights the factors that affect early AD detection. It concludes that further research on bio-markers is necessary for early AD detection. Optimization of classification techniques can help improve the classification accuracy to some extent. Combining the features obtained from different neuro-images including functional and structural MRI and PET images and other biomarkers can help to improve the prediction rate of MCI from normal patients.
  
Investigator's Name: Amera Almas
Proposed Analysis: Our goal in the research is a review on the various invasive and non-invasive biomarkers related to AD patients and the classification techniques used in the early diagnosis of Alzheimer’s disease. It highlights the factors that affect early AD detection. It concludes that further research on bio-markers is necessary for early AD detection. Optimization of classification techniques can help improve the classification accuracy to some extent. Combining the features obtained from different neuro-images including functional and structural MRI and PET images and other biomarkers can help to improve the prediction rate of MCI from normal patients.