Enduring CME Course: Can AI Help Physicians Detect Sepsis?

Activity ID

14727

Expires

October 21, 2028

Format Type

Enduring

CME Credit

0.5

Fee

$30

CME Provider: American Medical Association

Description of CME Course

Sepsis: at its inception, it is difficult to recognize but easy to treat; left unattended, it becomes easy to recognize and difficult to treat. As the adage states, sepsis is notoriously difficult to recognize in its early stages, due to the lack of a definitive diagnostic tool. When left undetected, the outcomes can be devastating. But what if artificial intelligence (AI) could be utilized to detect sepsis in its early stage? In this episode of Clinically Significantô, hosts Jodi Abbott, MD, MSc, MHCM, Maylyn Martinez, MD, MSc, and Avir Mitra, MD, explore the use of AI-tools for early detection of sepsis, including advancements as well as challenges to implementation and generalization.

Episode Guests:

Amy Hassell, MSN, BSN, RN: Chief Nursing Officer at UCHealth

CT Lin, MD: Chief Medical Information Officer (CMIO) at UCHealth-Colorado

Karandeep Singh, MD, MMSc: Jacobs Chancellor’s Endowed Chair and Chief Health AI Officer at UC San Diego Health

Clinically Significantô is hosted by:

Jodi Abbott, MD, MSc, MHCM: Professor of ObGyn at Boston University Chobanian & Avedisian School of Medicine and Medical Director of the Education Center Curriculum and Outreach for the American Medical Association (AMA)

Maylyn Martinez, MD, MSc: Assistant Professor of Medicine at the University of Chicago and former contributing host, writer, and producer for the JAMA Clinical Reviews podcast

Avir Mitra, MD: Associate Professor of Emergency Medicine at NYU Langone and contributing editor at Radiolab (WNYC).

Disclaimers

1. This activity is accredited by the American Medical Association.
2. This activity is free to AMA members.

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