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: | Peixin Lu |
| Institution: | Wuhan University |
| Department: | School of information management |
| Country: | |
| Proposed Analysis: | The fusion of complementary information contained in multi-modality data [e.g., magnetic resonance imaging (MRI), positron emission tomography (PET), and genetic data] has advanced the progress of automated Alzheimer’s disease (AD) diagnosis. However, multi-modality based AD diagnostic models are often hindered by the missing data, i.e., not all the subjects have complete multi-modality data. One simple solution used by many previous studies is to discard samples with missing modalities. However, this significantly reduces the number of training samples, thus leading to a sub-optimal classification model. The second approaches for dealing with this issue is imputing the missing values which uses various data imputation techniques (e.g., Zero imputation, k-Nearest Neighbor (KNN), expectation maximization, low-rank matrix completion, etc.) to impute the missing data, so that any diagnostic model that works with complete data can be used. However, this strategy could introduce unnecessary noise and thus reduce the classification performance. Furthermore, when building the classification model, most existing methods simply concatenate features from different modalities into a single feature vector without considering their underlying associations. I want to use the multi-modal data about Alzheimer in ADNI to develop an interpretable model or algorithm to solve the above problems to realize the early diagnosis and accurate diagnosis of Alzheimer. I am a doctoral student at Wuhan University. I want to use this project as my doctoral project. I have a rich foundation in computer learning and I believe I can complete this project well. If you can give me the opportunity to use this data, I would be very grateful. Thank you very much. Have a nice day. |
| Additional Investigators |
