Evidence map›Paper›PMID 39502891›Full record

ArticleJournal of clinical orthopaedics and trauma2024

Recent technological advancements in Artificial Intelligence for orthopaedic wound management.

Momna Sajjad Raja, Vinodhkumar Pannirselvam, Sriram Harish Srinivasan, Balasubramaniam Guhan, Faizal Rayan

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical orthopaedics and trauma, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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. Article
  2. Detection of Hypergranulation Tissue in Chronic Wound Images Using Artificial Intelligence Algorithms.Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Momna Sajjad RajaUniversity of Leicester, University Rd, Leicester, LE1 7RH, United Kingdom.
Vinodhkumar PannirselvamRoyal Stoke University Hospital, Stoke, United Kingdom.
Sriram Harish SrinivasanKettering General Hospital, Kettering, United Kingdom.
Balasubramaniam GuhanKettering General Hospital, Kettering, United Kingdom.
Faizal RayanKettering General Hospital, Kettering, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In orthopaedics, wound care is crucial as surgical site infections carry disease burden due to increased length of stay, decreased quality of life and poorer patient outcomes. Artificial Intelligence (AI) has a vital role in revolutionising wound care in orthopaedics: ranging from wound assessment, early detection of complications, risk stratifying patients, and remote patient monitoring. Incorporating AI in orthopaedics has reduced dependency on manual physician assessment which is time-consuming. This article summarises current literature on how AI is used for wound assessment and management in the orthopaedic community.

Indexed as

Artificial intelligenceDeep learningMachine learningOrthopaedicsWound care

Identifiers

PMID39502891
PMCPMC11532955

What OpenQuestion holds

Textmetadata
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.