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Meaningless Applications and Misguided Methodologies in Artificial Intelligence-Related Orthopaedic Research Propagates Hype Over Hope.
Ramkumar, Prem N; Pang, Michael; Polisetty, Teja; Helm, J Matthew; Karnuta, Jaret M.
Affiliation
  • Ramkumar PN; Orthopaedic Machine Learning Laboratory, Brigham & Women's Hospital, Boston, Massachusetts, U.S.A; Sports Medicine Service, Hospital for Special Surgery, New York, New York, U.S.A; Department of Orthopaedic Surgery, UTHealth McGovern Medical School, Houston, Texas, U.S.A. Electronic address: pre
  • Pang M; Orthopaedic Machine Learning Laboratory, Brigham & Women's Hospital, Boston, Massachusetts, U.S.A.
  • Polisetty T; Orthopaedic Machine Learning Laboratory, Brigham & Women's Hospital, Boston, Massachusetts, U.S.A.
  • Helm JM; Orthopaedic Machine Learning Laboratory, Brigham & Women's Hospital, Boston, Massachusetts, U.S.A.
  • Karnuta JM; Orthopaedic Machine Learning Laboratory, Brigham & Women's Hospital, Boston, Massachusetts, U.S.A; Department of Orthopaedic Surgery, University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.
Arthroscopy ; 38(9): 2761-2766, 2022 09.
Article in En | MEDLINE | ID: mdl-35550419
ABSTRACT
There exists great hope and hype in the literature surrounding applications of artificial intelligence (AI) to orthopaedic surgery. Between 2018 and 2021, a total of 178 AI-related articles were published in orthopaedics. However, for every 2 original research papers that apply AI to orthopaedics, a commentary or review is published (30.3%). AI-related research in orthopaedics frequently fails to provide use cases that offer the uninitiated an opportunity to appraise the importance of AI by studying meaningful questions, evaluating unknown hypotheses, or analyzing quality data. The hype perpetuates a feed-forward cycle that relegates AI to a meaningless buzzword by rewarding those with nascent understanding and rudimentary technical knowhow into committing several basic errors (1) inappropriately conflating vernacular ("AI/machine learning"), (2) repackaging registry data, (3) prematurely releasing internally validated algorithms, (4) overstating the "black box phenomenon" by failing to provide weighted analysis, (5) claiming to evaluate AI rather than the data itself, and (6) withholding full model architecture code. Relevant AI-specific guidelines are forthcoming, but forced application of the original Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis guidelines designed for regression analyses is irrelevant and misleading. To safeguard meaningful use, AI-related research efforts in orthopaedics should be (1) directed toward administrative support over clinical evaluation and management, (2) require the use of the advanced model, and (3) answer a question that was previously unknown, unanswered, or unquantifiable.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Orthopedics / Artificial Intelligence Type of study: Guideline / Prognostic_studies Limits: Humans Language: En Journal: Arthroscopy Journal subject: ORTOPEDIA Year: 2022 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Orthopedics / Artificial Intelligence Type of study: Guideline / Prognostic_studies Limits: Humans Language: En Journal: Arthroscopy Journal subject: ORTOPEDIA Year: 2022 Document type: Article
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