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: | Cesar Augusto Sanchez Villalobos |
| Institution: | Texas Tech University |
| Department: | Electrical And Computer Engineering |
| Country: | |
| Proposed Analysis: | During this project, we are going to use the provided data to generate an integrative analysis using transcriptomic data and neuroimages. To do that, we propose an innovative analysis influenced by the REFINED analysis (Bazgir et al) to work the transcriptomics, integrated with the information provided by the images. After preprocessing images and transcriptomics, we will apply Machine Learning algorithms to discriminate between control and AD groups. |
| Additional Investigators | |
| Investigator's Name: | Ahmed Bayoumi |
| Proposed Analysis: | The principal interest for Ahmed's Capstone project is to look into neuroimaging data and develop a discriminant to classify between CN and AD groups. This analysis is part of his capstone final project, he will feed a CNN with some of the images and create a baseline model for us, under my guidance. |
| Investigator's Name: | Ranadip Pal |
| Proposed Analysis: | During this project, we are going to use most of the provided data from the ADNI dataset. To do that, we propose an innovative analysis to work the gene expressions and convert the tabular data into images, integrated with the information provided by the scans. After preprocessing, we will apply Machine Learning algorithms to discriminate between control and dementia groups. |
| Investigator's Name: | Ruibo Zhang |
| Proposed Analysis: | During this project, we are going to use the provided data to generate an integrative analysis using transcriptomic data and neuroimages. To do that, we propose an innovative analysis influenced by the REFINED analysis (Bazgir et al) to work the transcriptomics, integrated with the information provided by the images. After preprocessing images and transcriptomics, we will apply Machine Learning algorithms to discriminate between control and AD groups |
| Investigator's Name: | Souparno Ghosh |
| Proposed Analysis: | During this project, we are going to use most of the provided data from the ADNI dataset. To do that, we propose an innovative analysis to work the gene expressions and convert the tabular data into images, integrated with the information provided by the scans. After preprocessing, we will apply Machine Learning algorithms to discriminate between control and dementia groups. |
| Investigator's Name: | Josh Lawrence |
| Proposed Analysis: | During this project, we are going to use most of the provided data from the ADNI dataset. To do that, we propose an innovative analysis to work the gene expressions and convert the tabular data into images, integrated with the information provided by the scans. After preprocessing, we will apply Machine Learning algorithms to discriminate between control and dementia groups. |
