Evidence map›Paper›PMID 37633507›Full record

ReviewThe Journal of arthroplasty2023

Educational Overview of the Concept and Application of Computer Vision in Arthroplasty.

Diana V Vera-Garcia, Fred Nugen, Sirwa Padash, Bardia Khosravi, John P Mickley, Bradley J Erickson, Cody C Wyles, Michael J Taunton

Abstract readReview
In one paragraph

Review in The Journal of arthroplasty, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Diana V Vera-GarciaOrthopedic Surgery Artificial Intelligence Laboratory (OSAIL), Mayo Clinic, Rochester, Minnesota; Radiology Informatics Laboratory (RIL), Department of Radiology, Mayo Clinic, Rochester, Minnesota.
Fred NugenOrthopedic Surgery Artificial Intelligence Laboratory (OSAIL), Mayo Clinic, Rochester, Minnesota; Radiology Informatics Laboratory (RIL), Department of Radiology, Mayo Clinic, Rochester, Minnesota.
Sirwa PadashOrthopedic Surgery Artificial Intelligence Laboratory (OSAIL), Mayo Clinic, Rochester, Minnesota; Radiology Informatics Laboratory (RIL), Department of Radiology, Mayo Clinic, Rochester, Minnesota.
Bardia KhosraviOrthopedic Surgery Artificial Intelligence Laboratory (OSAIL), Mayo Clinic, Rochester, Minnesota; Radiology Informatics Laboratory (RIL), Department of Radiology, Mayo Clinic, Rochester, Minnesota.
John P MickleyOrthopedic Surgery Artificial Intelligence Laboratory (OSAIL), Mayo Clinic, Rochester, Minnesota; Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
Bradley J EricksonRadiology Informatics Laboratory (RIL), Department of Radiology, Mayo Clinic, Rochester, Minnesota.
Cody C WylesOrthopedic Surgery Artificial Intelligence Laboratory (OSAIL), Mayo Clinic, Rochester, Minnesota; Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.
Michael J TauntonOrthopedic Surgery Artificial Intelligence Laboratory (OSAIL), Mayo Clinic, Rochester, Minnesota; Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota.

Funding

Resource CoreP30AR076312 · NIAMS · MAYO CLINIC ROCHESTER · PI Daniel Berry · 2019 to 2026
$5.5M
Precision Orthopedics: Multimodal Data Infrastructure for Personalized Surgical Decisions in Joint ArthroplastyR01AR073147 · NIAMS · MAYO CLINIC ROCHESTER · PI Hilal Maradit Kremers · 2018 to 2026
$3.5M
NIAMS NIH HHS P30 AR076312NIAMS NIH HHS R01 AR073147
6 · The paper itself

Abstract

Image data has grown exponentially as systems have increased their ability to collect and store it. Unfortunately, there are limits to human resources both in time and knowledge to fully interpret and manage that data. Computer Vision (CV) has grown in popularity as a discipline for better understanding visual data. Computer Vision has become a powerful tool for imaging analytics in orthopedic surgery, allowing computers to evaluate large volumes of image data with greater nuance than previously possible. Nevertheless, even with the growing number of uses in medicine, literature on the fundamentals of CV and its implementation is mainly oriented toward computer scientists rather than clinicians, rendering CV unapproachable for most orthopedic surgeons as a tool for clinical practice and research. The purpose of this article is to summarize and review the fundamental concepts of CV application for the orthopedic surgeon and musculoskeletal researcher.

Indexed as

Orthopedic ProceduresOrthopedicsArthroplastyComputersHumansartificial intelligencecomputer visiondata sciencedeep learningtotal hip arthroplastytotal knee arthroplasty

Identifiers

PMID37633507
PMCPMC10616773

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.