Editorial Commentary: Machine Learning and Artificial Intelligence Are Tools Requiring Physician and Patient Input When Screening Patients at Risk for Extended, Postoperative Opioid Use-Reference-Cited by-同舟云学术

Editorial Commentary: Machine Learning and Artificial Intelligence Are Tools Requiring Physician and Patient Input When Screening Patients at Risk for Extended, Postoperative Opioid Use

Published:2023-06 Issue:6 Volume:39 Page:1512-1514
ISSN:0749-8063
Container-title:Arthroscopy: The Journal of Arthroscopic & Related Surgery
language:en
Short-container-title:Arthroscopy: The Journal of Arthroscopic & Related Surgery

Author:

Lu Yining^ORCID,Mirle Vikranth^ORCID,Forsythe Brian^ORCID

Publisher

Elsevier BV

Subject

Orthopedics and Sports Medicine

Reference15 articles.

1. Machine learning model identifies preoperative opioid use, male sex, and elevated body mass index as predictive factors for prolonged opioid consumption following arthroscopic meniscal surgery;Castle;Arthroscopy,2023

2. Maradit Kremers H. How to develop and validate prediction models for orthopedic outcomes;Zaniletti;J Arthroplasty,2023

3. Machine learning algorithms predict achievement of clinically significant outcomes after orthopaedic surgery: A systematic review;Kunze;Arthroscopy,2022

4. 2020 Frank Stinchfield Award: Identifying who will fail following irrigation and debridement for prosthetic joint infection;Shohat;Bone Joint J,2020

5. Artificial intelligence and machine learning: an introduction for orthopaedic surgeons;Martin;Knee Surg Sports Traumatol Arthrosc,2022

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial Intelligence and Machine Learning May Resolve Health Care Information Overload;Arthroscopy: The Journal of Arthroscopic & Related Surgery;2024-06