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“When using AI-based approaches to analyze any kind of larger or multimodal data set, it is important to have a good understanding of the data set. If there are errors, the results will not be valid and clinically untranslatable if you are feeding the machine.”
In epilepsy, artificial intelligence (AI) algorithms may analyze electroencephalogram (EEG) signals for pre-seizure prediction. AI can also assess brain waves during seizure events to distinguish between different types of seizures. In particular, AI can analyze medical records and historical data, such as genetics and imaging, to create more personalized patient care plans.1
Kathryn A. Davis, MD, MSc, will be presenting the Possibilities of AI and the Possibilities of AI in the Field of Neurology at the Plenary Session of the 2023 American Academy of Neurology (AAN) Annual Meeting on April 22. will give a lecture. She is 27 years old and lives in Boston, Massachusetts. In her talk, she will discuss various challenges with using AI, such as bias in datasets and errors in data collection, as well as maintaining patient safety and data privacy. The rest of the session will cover the latest cutting-edge translational her research related to important clinical issues. Davis and her two other speakers will summarize recent findings and explain the importance of their clinical implications.
Prior to the conference, Davis, associate professor of neurology at the University of Pennsylvania and director of the Center for Penal Epilepsy, said: neurology live® outlines her presentation in an interview. She also talked about the challenges that can arise when using AI to analyze clinical trial data sets, and using her AI to help patients participate in research.
Click here for more information on the 2023 AAN.
