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: | Ali Deniz Çölgeçen |
Institution: | Zonguldak Bülent Ecevit University |
Department: | Faculty of Medicine |
Country: | |
Proposed Analysis: | Alzheimer's disease, the most common type of dementia, is one of the diseases that affect the cognitive and behavioral functions of people. It is one of the important neurodegenerative diseases of our age because of its only palliative treatment and the course of the disease. To provide as early diagnosis as possible considering the prognosis of the disease; It is of great importance in terms of many factors such as both the comfort of life of the patient and drug treatment, the burden of care, and the spiritual emotional state of the caregivers. In this project, other metabolic and metabolic diseases of Alzheimer's disease We aim to develop a diagnostic artificial intelligence that is able to distinguish between neurodegenerative diseases by examining various brain images. There are various literature studies and studies on disease detection in this area. However, our project is a first among its kind, as it will enable the synthesis of images taken with different techniques of many different brain regions. In our project, ROI, Cortical thickness feature extraction methods and CNN (Convolutional Artificial Neural Network) algorithm were used. With the success of this project, which makes a fast and reliable diagnosis, we can say that by diagnosing the disease earlier, we can reduce the financial and moral burden of Alzheimer's, which is a global problem, both to the individual and to his/her immediate surroundings. |
Additional Investigators | |
Investigator's Name: | Tuhan Oruk |
Proposed Analysis: | Alzheimer's disease, the most common type of dementia, is one of the diseases that affect the cognitive and behavioral functions of people. It is one of the important neurodegenerative diseases of our age because of its only palliative treatment and the course of the disease. To provide as early diagnosis as possible considering the prognosis of the disease; It is of great importance in terms of many factors such as both the comfort of life of the patient and drug treatment, the burden of care, and the spiritual emotional state of the caregivers. In this project, other metabolic and metabolic diseases of Alzheimer's disease We aim to develop a diagnostic artificial intelligence that is able to distinguish between neurodegenerative diseases by examining various brain images. There are various literature studies and studies on disease detection in this area. However, our project is a first among its kind, as it will enable the synthesis of images taken with different techniques of many different brain regions. In our project, ROI, Cortical thickness feature extraction methods and CNN (Convolutional Artificial Neural Network) algorithm were used. With the success of this project, which makes a fast and reliable diagnosis, we can say that by diagnosing the disease earlier, we can reduce the financial and moral burden of Alzheimer's, which is a global problem, both to the individual and to his/her immediate surroundings. |
Investigator's Name: | Hasan Sabri Elmas |
Proposed Analysis: | Alzheimer's disease, the most common type of dementia, is one of the diseases that affect the cognitive and behavioral functions of people. It is one of the important neurodegenerative diseases of our age because of its only palliative treatment and the course of the disease. To provide as early diagnosis as possible considering the prognosis of the disease; It is of great importance in terms of many factors such as both the comfort of life of the patient and drug treatment, the burden of care, and the spiritual emotional state of the caregivers. In this project, other metabolic and metabolic diseases of Alzheimer's disease We aim to develop a diagnostic artificial intelligence that is able to distinguish between neurodegenerative diseases by examining various brain images. There are various literature studies and studies on disease detection in this area. However, our project is a first among its kind, as it will enable the synthesis of images taken with different techniques of many different brain regions. In our project, ROI, Cortical thickness feature extraction methods and CNN (Convolutional Artificial Neural Network) algorithm were used. With the success of this project, which makes a fast and reliable diagnosis, we can say that by diagnosing the disease earlier, we can reduce the financial and moral burden of Alzheimer's, which is a global problem, both to the individual and to his/her immediate surroundings. |
Investigator's Name: | Berna Özdemir |
Proposed Analysis: | Alzheimer's disease, the most common type of dementia, is one of the diseases that affect the cognitive and behavioral functions of people. It is one of the important neurodegenerative diseases of our age because of its only palliative treatment and the course of the disease. To provide as early diagnosis as possible considering the prognosis of the disease; It is of great importance in terms of many factors such as both the comfort of life of the patient and drug treatment, the burden of care, and the spiritual emotional state of the caregivers. In this project, other metabolic and metabolic diseases of Alzheimer's disease We aim to develop a diagnostic artificial intelligence that is able to distinguish between neurodegenerative diseases by examining various brain images. There are various literature studies and studies on disease detection in this area. However, our project is a first among its kind, as it will enable the synthesis of images taken with different techniques of many different brain regions. In our project, ROI, Cortical thickness feature extraction methods and CNN (Convolutional Artificial Neural Network) algorithm were used. With the success of this project, which makes a fast and reliable diagnosis, we can say that by diagnosing the disease earlier, we can reduce the financial and moral burden of Alzheimer's, which is a global problem, both to the individual and to his/her immediate surroundings. |
Investigator's Name: | Buğrahan Mehmet Öztürk |
Proposed Analysis: | Alzheimer's disease, the most common type of dementia, is one of the diseases that affect the cognitive and behavioral functions of people. It is one of the important neurodegenerative diseases of our age because of its only palliative treatment and the course of the disease. To provide as early diagnosis as possible considering the prognosis of the disease; It is of great importance in terms of many factors such as both the comfort of life of the patient and drug treatment, the burden of care, and the spiritual emotional state of the caregivers. In this project, other metabolic and metabolic diseases of Alzheimer's disease We aim to develop a diagnostic artificial intelligence that is able to distinguish between neurodegenerative diseases by examining various brain images. There are various literature studies and studies on disease detection in this area. However, our project is a first among its kind, as it will enable the synthesis of images taken with different techniques of many different brain regions. In our project, ROI, Cortical thickness feature extraction methods and CNN (Convolutional Artificial Neural Network) algorithm were used. With the success of this project, which makes a fast and reliable diagnosis, we can say that by diagnosing the disease earlier, we can reduce the financial and moral burden of Alzheimer's, which is a global problem, both to the individual and to his/her immediate surroundings. |