An Approach to Visualize and Detect Features of Brain Injury Progression

Описание к видео An Approach to Visualize and Detect Features of Brain Injury Progression

We hosted two wonderful speakers, Dr. Baptiste Balança and Dr. Valentin Ghibaudo, for our April webinar.

Dr. Balança holds an MD in anesthesiology and a PhD in critical care neuroscience. He is an Associate Professor at the University of Lyon and works in the neurological anesthesiology and critical care departments of the Hospices Civils de Lyon. Dr. Ghibaudo holds a PhD and is a post doc at the Lyon neuroscience Research Center. He recently completed his thesis on fundamental neuroscience.

In their talk, the two explore how to visualize and analyze the interplay between markers of cortical injury such as cortical spreading depolarization and subcortical impairment such as heart rate and respiratory rate variability. They walk us through some neuromonitoring data processing in Python from scratch to event detection and visualization.

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 will focus on a real-world case study from us or from your colleagues. We will walk participants through the steps to re-create the analytics that answers the neurocritical care question presented. We’ll cover tools, data handling, feature engineering, cohort selection, model training, model tuning, visualization, and other topics. Sample code, Jupyter notebook, and data will be 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.

Website: https://www.moberganalytics.com
LinkedIn:   / moberg-analytics  
Twitter:   / moberganalytics  

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.

Комментарии

Информация по комментариям в разработке