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: | AKANKSHA PARIHAR |
| Institution: | RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA |
| Department: | ELECTRONICS AND COMMUNICATION ENGINEERING |
| Country: | |
| Proposed Analysis: | Detection of dementia at an early stage is very important to start the required treatment of the patients to prevent the disease from further growth. Classification of various stages of the disease can help us to identify the severity of the disease. In our work, the detection and classification of dementia will be performed using deep learning techniques. An intelligent model would be designed to calculate various features and relationships among them to reach any conclusion for detection and classification purposes. Deep Learning Techniques have the capability to perform the analysis of big data and extraction of desirable features. For this purpose, the ADNI dataset will help us to perform a detailed analysis in the above-mentioned area. Analysis of diseased participants' data will help us to detect and classify stages of dementia. Selection of various features to perform the classification can be done using basic signal processing and machine learning techniques. |
| Additional Investigators | |
| Investigator's Name: | PREETY D SWAMI |
| Proposed Analysis: | Detection of dementia at an early stage is very important to start the required treatment of the patients to prevent the disease from further growth. Classification of various stages of the disease can help us to identify the severity of the disease. In our work, the detection and classification of dementia will be performed using deep learning techniques. An intelligent model would be designed to calculate various features and relationships among them to reach any conclusion for detection and classification purposes. Deep Learning Techniques have the capability to perform the analysis of big data and extraction of desirable features. For this purpose, the ADNI dataset will help us to perform a detailed analysis in the above-mentioned area. Analysis of diseased participants' data will help us to detect and classify stages of dementia. Selection of various features to perform the classification can be done using basic signal processing and machine learning techniques. |
