PRESIDENTIAL SYMPOSIUM: Present and Future Applications of AI in Neurological Care and Research*
JEC
Time: 1:00 PM to 3:00 PM
Description
Recent advances in artificial intelligence are challenging our concepts of applied predictive medicine in clinical and research settings. Computer science can enhance the speed and efficiency of human directed data processing. It raises the prospect of achieving what approximates human thought in order to expedite, prioritize, and better assist in neurological clinical care and research decisions. In order to make best use of this incredible power and avoid unintended negative consequences, it is critically important that the path to AI output is understood. Data utilized by AI systems are accurate and robust when properly validated and applied by clinical or research end users. Speakers will present perspectives on current capabilities and future promise of computational tools for the application of implantable devices and the integration of multi-omics, imaging, and clinical data toward understanding the causes, prognosis and treatment of neurological disease.
Objectives
Assess current approaches to neurological treatment, diagnostics.
Describe how to apply medical data access and organization in ways that safely connect multiple medical institutions while preserving data privacy and intellectual property.
Discuss issues surrounding the use of AI in neurological care and research.
Speakers
AI Applications for Implantable Devices in Neuropsychiatric Diseases
DescriptionAn explosion of new hardware, software and AI technologies is rapidly energizing implantable and wearable neurodevices to diagnose, treat and manage brain network disorders. These devices are already communicating with the cloud, conversing with their hosts, tracking disease progression, and teaching us how our behavior affects our overall health. How will we use these powerful technologies, manage the huge floods of data they generate, and train clinicians to use them effectively? In this talk I will address these and other questions through examples of what clinical practice and training might look like in 2035.
SpeakersAI for Discovery and Diagnosis of Neurological Diseases using Deep Learning and Large-Scale Neuroimaging
DescriptionAI for Discovery and Diagnosis of Brain Diseases using Deep Learning and Large-Scale Neuroimaging.
SpeakersAI-Aided Analyses of Seizure and Interictal Phenotypes and Drug Responses in Epilepsy Models: Possibilities for Clinical Applications
DescriptionMachine learning-assisted 3D video analysis allows an unbiased assessment of epilepsy and anti-seizure drugs in preclinical models.
SpeakersThe Power of Informatics and Machine Learning Applications to Personalized Healthcare Delivery
DescriptionThe recent release of ChatGPT and other open-source large language models for generative artificial intelligence (AI) has created new awareness of the incredible acceleration of computational capabilities across numerous arenas, including healthcare.