{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"ATS Assemblies & Sections","title":"Elevator Pitch: Machine Learning to Predict Individualized Oxygenation Targets","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/f3f1bdff\"></iframe>","width":"100%","height":180,"duration":1190,"description":"In this episode of the Elevator Pitch, brought to you by the ATS Critical Care Assembly, we talk to Dr. Kevin Buell about his work using machine learning to predict optimal oxygenation targets for critically ill patients. \nHost: Divya Shankar, MD, Boston University \nGuest: Kevin Buell, MBBS, University of Chicago \n00:00 Introduction to the Podcast\n00:31 Meet Dr. Kevin Buell\n01:37 Dr. Buell's Research Interests\n02:08 Elevator Pitch: Oxygen Targets Study\n03:08 Study Methodology and Results\n05:08 Limitations and Machine Learning\n07:08 Model Validation and Application\n16:19 Future of Machine Learning in Medicine\n17:48 Conclusion and Takeaways\n19:13 Closing Remarks","thumbnail_url":"https://img.transistorcdn.com/9DaPUiuZAWF4aqHRUVM8yVGNq8O1aIe3EajK-tlwSGU/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS83OTVl/MDQ0ZDc5MGUwMThk/NDZkZjBhNWNmZTNm/NGZmOC5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}