Evidence map›Paper›PMID 36820427›Full record

ArticleJSES international2023

Research on artificial intelligence in shoulder and elbow surgery is increasing.

Puneet Gupta, Erick M Marigi, Joaquin Sanchez-Sotelo

Open access · goldAbstract read
In one paragraph

Article in JSES international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 21% of its field
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
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

3 authors at 2 institutions in 1 country.

Puneet GuptaDepartment of Orthopaedic Surgery, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
Erick M MarigiDepartment of Orthopaedic Surgery, Mayo Clinic, Rochester, MN, USA.
Joaquin Sanchez-SoteloDepartment of Orthopaedic Surgery, Mayo Clinic, Rochester, MN, USA.
Mayo Clinic in Arizona · USGeorge Washington University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Total health care spending in the United States is increasing. In order to improve our delivery of high-quality, patient-centric, and cost-effective care, artificial intelligence (AI) and its subsets are being increasingly explored and utilized in medicine. Applications of AI in orthopedic surgery, including shoulder and elbow surgery, are being actively studied and have stirred much discussion. However, the trends of research on AI applications in shoulder and elbow surgery have not yet been quantified. Thus, the purpose of this study is to explore the general trends of research in applying AI to shoulder and elbow surgery and to examine characteristics of these research publications. Methods: A literature search was conducted using PubMed for all articles published between January 1, 2000 and May 12, 2022. The primary search query used was as follows: (shoulder) and (AI OR machine learning OR deep learning OR neural networks). Exclusion criteria were as follows: (1) not pertinent to orthopedic surgeons (2) not pertaining to shoulder or elbow surgery, and (3) not pertaining to AI, machine learning, and deep learning. Selected articles in high-impact and relevant orthopedic journals were further characterized and analyzed. Results: The annual number of articles increased from 1 article in 2006 to 24 articles in 2021. There was a 4-fold increase in publications between 2019 and 2021, and a 6-fold increase between 2018 and 2021. The average number of publications per year increased exponentially from 2010 to 2021 (R2 = 0.608; Conclusion: This study provides quantitative evidence for the first time that publications applying AI and its subsets to shoulder and elbow surgery are growing exponentially since the year 2010, with the most rapid growth beginning between the years of 2019 and 2020.

Indexed as

Artificial intelligenceDeep learningElbowMachine learningShoulderTrends

Identifiers

PMID36820427
PMCPMC9937849
OpenAlexW4308148976

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.