Postmarket surveillance of arthroplasty device components using machine learning methods-Reference-Cited by-同舟云学术

Postmarket surveillance of arthroplasty device components using machine learning methods

Published:2019-08-16 Issue:11 Volume:28 Page:1440-1447
ISSN:1053-8569
Container-title:Pharmacoepidemiology and Drug Safety
language:en
Short-container-title:Pharmacoepidemiol Drug Saf

Author:

Cafri Guy¹^ORCID,Graves Stephen E.²,Sedrakyan Art³,Fan Juanjuan⁴,Calhoun Peter⁵,Steiger Richard N.⁶,Cuthbert Alana²,Lorimer Michelle²,Paxton Elizabeth W.¹

Affiliation:

1. Surgical Outcomes and AnalysisKaiser Permanente San Diego CA

2. Australian Orthopaedic Association National Joint Replacement Registry Adelaide South Australia Australia

3. Healthcare Policy and ResearchWeill Cornell Medical College New York City NY

4. Department of Mathematics and StatisticsSan Diego State University San Diego CA

5. Computational Science Research CenterSan Diego State University San Diego CA

6. Department of Surgery Epworth HealthCareUniversity of Melbourne Melbourne Victoria Australia

Publisher

Wiley

Subject

Pharmacology (medical),Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/pds.4882

Reference32 articles.

1. Recalls and Safety Alerts Affecting Automated External Defibrillators

2. Semper Fidelis — Consumer Protection for Patients with Implanted Medical Devices

3. Postmarketing Surveillance of Medical Devices — Filling in the Gaps

4. Metal-on-metal failures—in science, regulation, and policy

5. Centers for Disease Control and Prevention (CDC).National Center for Health Statistics. National Hospital Discharge Survey: 2010 table Procedures by selected patient characteristics ‐ Number by procedure category and age. CDC web site.http://www.cdc.gov/nchs/fastats/inpatient‐surgery.htm. 2013.

Cited by 8 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. Can Machine Learning Algorithms Contribute to the Initial Screening of Hip Prostheses and Early Identification of Outliers?;Prosthesis;2024-06-26

2. What Is the Most Appropriate Comparator to Use in Assessing the Comparative Performance of Primary Total Knee Prostheses? A Registry-Based Study;Arthroplasty Today;2024-06

3. Supervised machine learning for the prediction of post‐operative clinical outcomes of hip and knee replacements: a review;ANZ Journal of Surgery;2024-04-10

4. What is the most appropriate comparator group to use in assessing the performance of primary total hip prostheses within the community?;HIP International;2023-12-12

5. Concerns surrounding application of artificial intelligence in hip and knee arthroplasty;The Bone & Joint Journal;2022-12-01