Artificial Intelligence for the Clinician Episode 3: Basics of Machine Learning Statistics

Behind The Knife: The Surgery Podcast

Science, Health & Fitness, Medicine, Education

4.8 • 1.4K Ratings

🗓️ 4 September 2025

⏱️ 25 minutes

🔗️ Recording | iTunes | RSS

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Summary

Welcome back our series on AI for the clinician! In this episode, we go over some basics of machine learning statistics with the goal to help you read and analyze contemporary studies. Some of this will be a review, and parts will be technical, but by the end we hope reading these studies is less daunting.

Hosts:
Ayman Ali, MD
Ayman Ali is a Behind the Knife fellow and general surgery PGY-4 at Duke Hospital in his academic development time where he focuses on data science, artificial intelligence, and surgery.

Julie Doberne, MD, PhD: @juliedoberne
Julie Doberne is an Assistant Professor of Surgery, Assistant Professor of Medical Informatics and Clinical Epidemiology, cardiothoracic surgeon, and faculty member of the Surgical Data and Decision Sciences Lab at Oregon Health and Science University.

Phillip Jenkins, MD: @PhilJenkinsMD
Phil Jenkins is a general surgery PGY-4 at Oregon Health and Science University and a National Library of Medicine Post-Doctoral fellow pursuing a master’s in clinical informatics.

Steven Bedrick, PhD: @stevenbedrick

Steven Bedrick is a machine learning researcher and an Associate Professor in Oregon Health and Science University’s Department of Medical Informatics and Clinical Epidemiology.

Shelby Willis, MD
Shelby Willis is a general surgery PGY-4 at Oregon Health and Science University. She is currently in her research time in the Surgical Data and Decision Sciences lab at OHSU pursuing advanced training in informatics.

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Transcript

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0:00.0	Behind the Night, the Surgery Podcast, relevant and engaging content designed to help you dominate the day. We are proud to announce a comprehensive update to our general surgery oral board review content, covering all of the latest score curriculum.
0:32.9	We now have 123 up-to-date audio scenarios, all with expert commentary, 10 interactive video scenarios
0:39.7	to test your knowledge, and 97 comprehensive operative descriptions that will have you
0:45.5	smooth-talking your way through the exam. It's all accessible via our top-notch iOS and Android
0:51.2	apps, and all for hundreds of dollars less than other review courses.
0:56.1	It's the best content at maximum value.
0:59.2	Learn more at behind the knife.org.
1:01.5	Hey everyone. I'm an only one of the surgical education fellows.
1:04.9	Welcome back to artificial intelligence for the clinician here on Behind the Knife.
1:08.7	This episode is going to be about statistics and specifically
1:11.3	how to interpret and read the results of a machine learning study. This will be technical,
1:16.8	but hopefully fun and relevant to modern surgery and medicine. New tools will incorporate AI,
1:22.6	and they already do, like radiology interpreters. And we have to be able to understand the
1:27.0	evidence to evaluate them and use them, just like
1:29.8	we do for every other diagnostic tool and test.
1:33.1	So to talk about this topic, we're here today with a couple of the fantastic team members
1:37.0	at OHSU.
1:38.3	First, I'm going to welcome Phil Jenkins, a general surgery resident and National Library
1:43.2	of Medicine Postdoc. Phil, welcome back.
1:47.1	Thanks. Glad to be back. Looking forward to this one. And joining us for the first time is Shelby Willis,
1:52.6	another general surgery resident at OHS here. Thanks. excited to be joining the series.
1:58.8	And we also have Dr. Julie Dober and a cardiac surgeon and informatician at OHS here.
	...

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