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: | Miaochun Cai |
| Institution: | Guangdong Provincial Hospital of Chinese Medicine |
| Department: | Research Group of Standardization of Chinese Medic |
| Country: | |
| Proposed Analysis: | With the rapid aging of population, the morbidity of Alzheimer’s diseases grows, bringing heavier economic burden meanwhile threatening human health. In order to identify people at higher risk of Alzheimer’s diseases and take timely interventions to prevent or cure them, better understanding to their relevant risk factors is a necessity. The purpose of our research is to discover risk factors and biomarkers relevant to different Alzheimer’s diseases with brain neuroimaging, genetic and biochemical data, and explore the interaction among risk factors and their relationship with Alzheimer’s diseases, using mathematical models based on machine learning algorithms. The large amount of clinical, imaging and genetic data provided by ADNI makes it possible to deepen our understanding into the interaction and causality of different risk factors in the pathophysiological mechanism of Alzheimer’s diseases. Consistent with the aims of the ADNI, this research will hopefully provide new models for the diagnosis, classification, prevention and prognosis of Alzheimer’s diseases, helping medical professionals accurately recognize the risk of Alzheimer’s diseases and understand the pathogenic mechanism, furthermore laying basis for discovery of better diagnosis and treatment to Alzheimer’s diseases. |
| Additional Investigators | |
| Investigator's Name: | Wenjia Chen |
| Proposed Analysis: | With the rapid aging of population, the morbidity of Alzheimer’s diseases grows, bringing heavier economic burden meanwhile threatening human health. In order to identify people at higher risk of Alzheimer’s diseases and take timely interventions to prevent or cure them, better understanding to their relevant risk factors is a necessity. The purpose of our research is to discover risk factors and biomarkers relevant to different Alzheimer’s diseases with brain neuroimaging, genetic and biochemical data, and explore the interaction among risk factors and their relationship with Alzheimer’s diseases, using mathematical models based on machine learning algorithms. The large amount of clinical, imaging and genetic data provided by ADNI makes it possible to deepen our understanding into the interaction and causality of different risk factors in the pathophysiological mechanism of Alzheimer’s diseases. Consistent with the aims of the ADNI, this research will hopefully provide new models for the diagnosis, classification, prevention and prognosis of Alzheimer’s diseases, helping medical professionals accurately recognize the risk of Alzheimer’s diseases and understand the pathogenic mechanism, furthermore laying basis for discovery of better diagnosis and treatment to Alzheimer’s diseases. |
| Investigator's Name: | Hui Li |
| Proposed Analysis: | With the rapid aging of population, the morbidity of Alzheimer’s diseases grows, bringing heavier economic burden meanwhile threatening human health. In order to identify people at higher risk of Alzheimer’s diseases and take timely interventions to prevent or cure them, better understanding to their relevant risk factors is a necessity. The purpose of our research is to discover risk factors and biomarkers relevant to different Alzheimer’s diseases with brain neuroimaging, genetic and biochemical data, and explore the interaction among risk factors and their relationship with Alzheimer’s diseases, using mathematical models based on machine learning algorithms. The large amount of clinical, imaging and genetic data provided by ADNI makes it possible to deepen our understanding into the interaction and causality of different risk factors in the pathophysiological mechanism of Alzheimer’s diseases. Consistent with the aims of the ADNI, this research will hopefully provide new models for the diagnosis, classification, prevention and prognosis of Alzheimer’s diseases, helping medical professionals accurately recognize the risk of Alzheimer’s diseases and understand the pathogenic mechanism, furthermore laying basis for discovery of better diagnosis and treatment to Alzheimer’s diseases. |
