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Machine Learning for the Experienced Orthopaedic Reviewer: It May Not Be as Confusing as You Think Reviewer Workshop from - July 2023 AOSSM Annual Meeting
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Journal Reviewers' Workshop
Machine Learning for the Experienced Orthopaedic Reviewer: It May Not Be as Confusing as You Think

This presentation is a recorded capture from Reviewer Workshop on July 13, 2023 in Washington, DC at the AOSSM Annual Meeting.

 

David C. Landy, MD, PhD
Associate Editor for Clinical Trials and Statistics, American Journal of Sports Medicine

 

Learning objectives:

1. Participants will gain an appreciation for the distinction between inference and prediction and how these concepts are related to the selection of analytic methods and presentation of results.

2. Participants will review the basics of regression and understand how newer machine learning algorithms are both similar and dissimilar from these more familiar techniques. 

3. Participants will consider how the review of research presenting the results of machine learning algorithms requires continued consideration of the surrounding clinical context.


 

ACCREDITATION STATEMENT The American Orthopaedic Society for Sports Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

AMA CREDIT DESIGNATION STATEMENT The American Orthopaedic Society for Sports Medicine designates this enduring material for a maximum of 0.5 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CLAIMING CREDIT In order to obtain AMA PRA Category 1 Credits™ participants must complete the activity and evaluation. Please note that this is an online-only activity. Participants must complete the activity and evaluation online. No hard copy submissions will be accepted.

DISCLOSURE STATEMENT In accordance with the guidelines of the ACCME, it is the policy of the AOSSM that faculty and planners disclose to the learners all financial relationships during the past twelve months with any commercial interest (any entity producing, marketing, re-selling, or distributing health care goods and services consumed by, or used on, patients). In accordance with AOSSM policy, faculty participation is predicated upon timely submission and review of AOSSM disclosures. Non-compliance results in faculty being stricken from the program.

Additional resources for further study:

1. Ramkumar PN, Luu BC, Haeberle HS, Karnuta JM, Nwachukwu BU, Williams RJ. Sports Medicine and Artificial Intelligence: A Primer. Am J Sports Med. 2022 Mar;50(4):1166-1174.

2. Ley C, Martin RK, Pareek A, Groll A, Seil R, Tischer T. Machine learning and conventional statistics: making sense of the differences. Knee Surg Sports Traumatol Arthrosc. 2022 Mar;30(3):753-757.

3. Andriy Burkov. The Hundred-Page Machine Learning Book. 2019.

Summary
Availability: On-Demand
Expires on 08/30/2026
Cost: FREE
Credit Offered:
0.5 CME Credit
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