AI in EM – Part 3: Skynet Hasn’t Got A Chance!

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EM Pulse Podcast™

UC Davis Department of Emergency Medicine

189 episodes

3 days ago

We invite you to join us on EM Pulse Podcast™ as we delve into current topics in Emergency Medicine through fascinating cases, interviews with authors of groundbreaking research, and discussion with clinical experts in adult and pediatric EM. Let’s learn together from these amazing people who are changing the landscape of clinical care.

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AI in EM – Part 3: Skynet Hasn’t Got A Chance!

EM Pulse Podcast™

35 minutes 41 seconds

9 months ago

AI in EM – Part 3: Skynet Hasn’t Got A Chance!

In this final installment of our three-part series on artificial intelligence in emergency medicine, we explore the rapid expansion of AI and its implications for clinical practice. In previous episodes, we explored how AI is revolutionizing tasks like diagnosis, treatment planning, and patient monitoring. In this final chapter, guest expert, Dr. Brian Patterson, joins us to discuss how to safely integrate AI into clinical practice. We recap insights from previous episodes, including AI’s transformative potential and real-world applications, while diving into the challenges and regulatory efforts shaping this exploding field. Whether you’re an AI skeptic or an early adopter, this episode unpacks what you need to know about integrating AI safely and effectively into emergency medicine.

How are you using AI in your ED? What are your concerns and hopes for the future of AI in medicine? Keep the discussion going on social media @empulsepodcast or at ucdavisem.com

Hosts:

Dr. Julia Magaña, Professor of Pediatric Emergency Medicine at UC Davis

Dr. Sarah Medeiros, Associate Professor of Emergency Medicine at UC Davis

Guest:

Dr. Brian Patterson, Associate Professor Emergency Medicine and Physician Administrative Director of Clinical AI at the University of Wisconsin.

Resources:

Liao F, Adelaine S, Afshar M, Patterson BW. Governance of Clinical AI applications to facilitate safe and equitable deployment in a large health system: Key elements and early successes. Front Digit Health. 2022 Aug 24;4:931439. doi: 10.3389/fdgth.2022.931439. PMID: 36093386; PMCID: PMC9448877.

Mello MM, Guha N. Understanding Liability Risk from Using Health Care Artificial Intelligence Tools. N Engl J Med. 2024 Jan 18;390(3):271-278. doi: 10.1056/NEJMhle2308901. PMID: 38231630.

OpenEvidence.com
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Thank you to the UC Davis Department of Emergency Medicine for supporting this podcast and to Orlando Magaña at OM Productions for audio production services.