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: | Stepan Hlushak |
| Institution: | Nanostics Inc. |
| Department: | Technology |
| Country: | |
| Proposed Analysis: | We are mainly interested in the TADPOLE dataset. The dataset will be used to test our implementation of the Graph Convolutional Networks (GCN) for disease prediction. Recent latent graph learning GCN approaches described in Refs. 1 and 2 show great promise in computer aided diagnosis. Both of these recent works use the TADPOLE dataset for evaluation of the model performance. Thus, without the data it will be impossible for us to verify the correctness of our implementation. Our aim is to implement and evaluate aforementioned GCN for possible commercialization. References 1. Cosmo L, Kazi A, Ahmadi SA, Navab N, Bronstein M. Latent-graph learning for disease prediction. InInternational Conference on Medical Image Computing and Computer-Assisted Intervention 2020 Oct 4 (pp. 643-653). Springer, Cham. 2. Zheng S, Zhu Z, Liu Z, Guo Z, Liu Y, Zhao Y. Multi-modal Graph Learning for Disease Prediction. arXiv preprint arXiv:2107.00206. 2021 Jul 1. |
| Additional Investigators |
