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Principal Investigator  
Principal Investigator's Name: Aamna AlShehhi
Institution: Khalifa University of Science and Technology - MIT
Department: Biomedical Engineering
Proposed Analysis: Our goal is to apply advance interoperability algorithms on ADNI as a pathway to develop hypotheses and validate Alzheimer’s disease prediction and disease risk factors. We propose to develop a multi-Input deep learning model to improve the predictions, and to investigate the covariates that influence the model. The integration of deep learning will increase our understanding of AD progression and the factors that affected it. Following two specific aims: AIM 1: Improvement the predications from MCI to AD. AIM 2: Identification of different AD-related risk factors. General Methodology, we will follow: 1. Handling Missing Value using Autoencoder. 2. Hyperparameter Optimization using Bayesian optimization [gaussian processes ] 3. Multi-Input Model: a deep model which take combination of EHR, Images and text as input and logit of AD as an output. 4. Risk-Factor Interpretation using a risk backpropagation 5. Performance Measuring and Evaluation using accuracy, AUC,and F1-score (on a test set) Please not: Currently I also a post-doc researcher at Khalifa University and MIT(Email: alshehhi@mit.edu)
Additional Investigators  
Investigator's Name: Ferial J. Abuhantash
Proposed Analysis: Working on the Proposed Analysis
Investigator's Name: Mohd Hantash
Proposed Analysis: Working on the Proposed Analysis by the PI
Investigator's Name: Raluca-Ioana Cobzaru
Proposed Analysis: same as the main PI
Investigator's Name: georioan georioan
Proposed Analysis: As proposed in the main page
Investigator's Name: anastasia ntracha
Proposed Analysis: As proposed on the main page