Integrating Personalized Brain Simulation, Machine Learning, and Multimodal Neuroimaging for Early Detection of Alzheimer's Disease: A New Data-Driven Methodological Framework
Description: Maintaining a healthy brain through one's lifespan depends on the complex interaction between the brain, genetics, and lifestyle. With a rapidly aging population, the prevalence of neurodegenerative diseases like Alzheimer's Disease are significantly increasing, with a projected 107 million cases by 2050. This is now recognized as one of the major medical challenges facing the world in the 21st century. While treatment options are limited, early detection can allow prevention strategies to provide individuals with additional years of healthy living, significantly less burden on their loved ones, and a substantial reduction in healthcare costs. Current early detection methods mainly limited to inherited types of early-onset Alzheimer's Disease. Our goal is to greatly improve early detection of all types of Alzheimer's Disease. This project will, for the first time, integrate personalized brain simulation and the predictive power of artificial intelligence to improve our understanding of Alzheimer's Disease, to predict as early as possible who will develop the disease, and even to forecast what form it will take for each individual. Breakthroughs in personalized brain simulation, a type of mathematical brain modelling that is tuned to each individual, have already been used to show how and why the brain changes when inflicted with Alzheimer's Disease. We will use high-quality clinical databases that follow the development of thousands of individuals through the aging process in research that can lead to new clinical detection methods. We will use brain simulation to model the effects of Alzheimer's other dementias compared to healthy aging on each person's brain, and we will use artificial intelligence to discover changes in the brain that predict a diagnosis of Alzheimer's in later years. With this new data-driven approach, we aim to help add years of high quality of life for the millions of people who may be affected by Alzheimer's in the future, and their families.
Amount: CA$150,000
Funding type: fellowship
Funder scheme: CIHR Fellowship
Start date: 2020-06-01
End date: 2023-05-31
Investigator: Jaskiret Dhindsa
Institution: Charite - Universitatsmedizin Berlin (Germany)
Funded outputs count: 0
Funder award ID: 171201_1
OpenAlex ID: G275147883