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: | Chanati Jantrachotechatchawan |
| Institution: | Mahidol University |
| Department: | Faculty of Medicine Siriraj Hospital |
| Country: | |
| Proposed Analysis: | We will be creating a deep-learning model to predict 1) disease stages (NC, MCI, AD), 2) CSF biomarker levels, and 3) representations of FDG PET images for clinical diagnosis and study of AD subtypes using blood-based multi-omic data including 1) RNA transcription (microarray and possibly RNA-seq), 2) DNA methylation (450k), and potentially 3) protein levels (Luminex multiplex) as inputs. Data are subset into train, validation, and evaluation sets by patient IDs. Longitudinal data from ADNI would greatly facilitate model understanding of disease progression. |
| Additional Investigators | |
| Investigator's Name: | Kobchai Duangrattanalert |
| Proposed Analysis: | We are working as a team on the same project as described in Chanati's proposed analysis --- We will be creating a deep-learning model to predict 1) disease stages (NC, MCI, AD), 2) CSF biomarker levels, and 3) representations of FDG PET images for clinical diagnosis and study of AD subtypes using blood-based multi-omic data including 1) RNA transcription (microarray and possibly RNA-seq), 2) DNA methylation (450k), and potentially 3) protein levels (Luminex multiplex) as inputs. Data are subset into train, validation, and evaluation sets by patient IDs. Longitudinal data from ADNI would greatly facilitate model understanding of disease progression. |
| Investigator's Name: | Airin Intaratat |
| Proposed Analysis: | *Note: Airin Intaratat is the first author/main researcher of this project with Chanati J and Kobchai D as co-supervisors. Airin is currently a high-school student and since this status is not available to select in the form, we opted for a B.A. instead We are working as a team on the same project as described in Chanati's proposed analysis --- We will be creating a deep-learning model to predict 1) disease stages (NC, MCI, AD), 2) CSF biomarker levels, and 3) representations of FDG PET images for clinical diagnosis and study of AD subtypes using blood-based multi-omic data including 1) RNA transcription (microarray and possibly RNA-seq), 2) DNA methylation (450k), and potentially 3) protein levels (Luminex multiplex) as inputs. Data are subset into train, validation, and evaluation sets by patient IDs. Longitudinal data from ADNI would greatly facilitate model understanding of disease progression. |
