WAVEFRONT: Noninvasive, Automated Detection of Cortical Spreading Depolarizations Using Scalp EEG
🌟🎙️ For the December installation of our webinar, Case Studies in Neurocritical Care AI, we were honored to host Dr. Alireza Chamanzar and John McNamee from Precision Neuroscopics! (https://www.precisionneuroscopics.com)
Talk Title: WAVEFRONT: A Noninvasive, Automated Detection Technique for Cortical Spreading Depolarizations Using Scalp EEG
✨ Dr. Alireza Chamanzar, PhD, with a background in electrical and computer engineering from Carnegie Mellon, developed WAVEFRONT and other patented neuro-diagnostic algorithms like SilenceMap and CSD-STGAT. He is the CTO of Precision Neuroscopics and an assistant professor at the University of Pittsburgh, where he advances AI in healthcare at the Computational Pathology & AI Center of Excellence (CPACE).
John McNamee, a Biomedical Engineer specializing in Neural Engineering, holds degrees from the University of Florida and Carnegie Mellon. With experience in neural signal processing and biotech startups, he now works as a software engineer at Precision Neuroscopics, advancing WAVEFRONT as a practical tool for researchers and clinicians.
🎙️ About the Talk:
‼️ WAVEFRONT is a non-invasive, automated method for detecting cortical spreading depolarizations using scalp EEG. Validated on 32 patients with various brain injuries (TBI, SAH, MHS) across a multicenter cohort, it achieves up to 88.6% detection with less than 4% false alarms, even under challenging conditions like missing skulls. Its intuitive GUI enables users to review detections, temporal and spatial signal patterns, propagation speed, and CSD frequency over time. 🧠
If you're interested in joining the webinar series, please register via this link: https://us06web.zoom.us/webinar/regis...
You can view recordings of past webinars here: • Webinar Series - AI in Neurocritical ...
This webinar series is designed to help clinicians learn how to get more from their neurocritical care data. No prior experience is necessary.
Each session focuses on a real-world case study from us or from your colleagues. We walk participants through the steps to re-create the analytics that answers the neurocritical care question presented. We cover tools, data handling, feature engineering, cohort selection, model training, model tuning, visualization, and other topics. Sample code, Jupyter notebook, and data are provided to enable you to experiment and apply these methods to your own data sets and problems.
Please feel free to let us know if you have any questions about the concepts that were presented in this video or if you have case studies or suggestions for upcoming sessions.
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Disclaimer:
The views and opinions expressed by the presenter and other third parties do not necessarily reflect those of Moberg Analytics, Inc. Moberg Analytics, Inc. makes no clinical claims regarding information described by the presenter and other third parties.
