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: | Lifang He |
Institution: | Lehigh University |
Department: | Department of Computer Science and Engineering |
Country: | |
Proposed Analysis: | We are currently working on developing explainable machine learning models for interpretable prediction. We plan to use data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to test and evaluate our proposed methods. The overarching goal of this project is to develop novel multi-modal deep learning methods to intuitively and intelligently connect, analyze and interpret brain imaging genomics data. Our specific objectives are the following. (1) Develop a multi-modal deep learning framework for joint quantification of brain imaging and genomic biomarkers as well as improving the diagnosis and prognosis of Alzheimer's disease. (2) Build a deep graph model with multi-scale learning for fully utilizing topological information within and across multiple brain networks from imaging and genomics. (3) Design methods to optimize the interpretability of predictions to uncover imaging-genomics associations and phenotype-biomarker associations using ADNI dataset. |
Additional Investigators | |
Investigator's Name: | Zhaoming Kong |
Proposed Analysis: | He is my PhD student and will work on develop explainable tensor neural network methods for disease prediction, as well as uncovering imaging-genomics associations and phenotype-biomarker associations. |
Investigator's Name: | Jun Yu |
Proposed Analysis: | He is my PhD student and will work on develop explainable multi-task learning methods for disease prediction and progression, as well as uncovering imaging-genomics associations and phenotype-biomarker associations. |
Investigator's Name: | Houliang Zhou |
Proposed Analysis: | He is my PhD student and will work on develop explainable graph neural network methods for disease prediction and progression, as well as uncovering imaging-genomics associations and phenotype-biomarker associations. |