[HT-06] Neuroimaging diagnosis based on databases and AI in the near future

[HT-06-3] Neuroimaging and Informatics in Alzheimer's disease Research

Arthur W. Toga (USC Mark and Mary Stevens Neuroimaging and Informatics Institute, USA)

Artificial intelligence (AI) is an emerging technology having potentials for real-world applications to many fields including medicine. The application of AI to imaging data from neurological disorders may open a new era for the diagnosis of neuro-psychiatric disorders. However, to make AI effective, we need to have an access to a high-quality imaging database. In this symposium, we will discuss the current states of large clinical database, current application of AI technology to neuroimaging data, and cutting-edge imaging analysis to increase the chance of retrieving useful information from imaging data. Through this symposium, audience will be able to imagine AI-assisted imaging diagnosis of neurological disorders in the near future.

Arthur W. Toga, PhD, is a provost professor with a primary appointment in the Department of Ophthalmology and director of the USC Mark and Mary Stevens Neuroimaging and Informatics Institute. His research is focused on neuroimaging, informatics, mapping brain structure and function, and brain atlasing. Dr. Toga has developed multimodal imaging and data aggregation strategies and applied them in a variety of neurological diseases and psychiatric disorders. His work in informatics includes the development and implementation of some of the largest and most widely used databases and data mining tools linking disparate data from genetics, imaging, clinical and behavior, supporting global efforts in Alzheimer’s disease, Huntington’s and Parkinson’s disease. His work also includes measurement of the dynamic brain during development and aging, and as a result of insult. For example, his studies include changes following traumatic brain injury and sensory deprivation on the connectome.

In addition, Dr. Toga’s groups have initiated studies to answer fundamental questions in the relationship between eye disease and its relationship to the central visual processing. His work, combining advanced retinal imaging with the brain-mapping techniques developed in the Human Connectome Project using novel yet robust analytical methods, may help answer these questions.