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  • ACTIVE INVESTIGATIONS Search for current projects using the investigator's name, institution, or keywords.
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Active Investigations

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: Harshad Shah
Institution: Mukesh Patel School Of Technology Management and Engineering
Department: Artificial Intelligence
Country:
Proposed Analysis: Our project will use the ADNI dataset to train and evaluate a deep learning model for Alzheimer's Disease detection. The project will use a variety of deep learning techniques to train and evaluate the model. The ADNI dataset is crucial for the project because it is a large, well-annotated dataset of brain images from patients with Alzheimer's disease and healthy controls. GANs will be used to generate new images of brain scans that are similar to the images in the ADNI dataset. These new images can then be used to train the deep learning model, which could improve its accuracy.
Additional Investigators  
Investigator's Name: Viraj Patil
Proposed Analysis: Our project will use the ADNI dataset to train and evaluate a deep learning model for AD detection. The project will use a variety of deep learning techniques to train and evaluate the model. The ADNI dataset is crucial for the project because it is a large, well-annotated dataset of brain images from patients with Alzheimer's disease and healthy controls. GANs will be used to generate new images of brain scans that are similar to the images in the ADNI dataset. These new images can then be used to train the deep learning model, which could improve its accuracy.
Investigator's Name: Disha Reddy
Proposed Analysis: Our project will use the ADNI dataset to train and evaluate a deep learning model for AD detection. The project will use a variety of deep learning techniques to train and evaluate the model. The ADNI dataset is crucial for the project because it is a large, well-annotated dataset of brain images from patients with Alzheimer's disease and healthy controls. GANs will be used to generate new images of brain scans that are similar to the images in the ADNI dataset. These new images can then be used to train the deep learning model, which could improve its accuracy.