Evidence map›Paper›PMID 38026475›Full record

ReviewFrontiers in surgery2023

ChatGPT in orthopedics: a narrative review exploring the potential of artificial intelligence in orthopedic practice.

Riccardo Giorgino, Mario Alessandri-Bonetti, Andrea Luca, Filippo Migliorini, Nicolò Rossi, Giuseppe M Peretti, Laura Mangiavini

Abstract readReview
In one paragraph

Review in Frontiers in surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

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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

7 authors.

Riccardo GiorginoIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Mario Alessandri-BonettiDepartment of Plastic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, United States.
Andrea LucaIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Filippo MiglioriniDepartment of Orthopaedic, Trauma, and Reconstructive Surgery, RWTH University Medical Centre, Aachen, Germany.
Nicolò RossiIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Giuseppe M PerettiIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
Laura MangiaviniIRCCS Istituto Ortopedico Galeazzi, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The field of orthopedics faces complex challenges requiring quick and intricate decisions, with patient education and compliance playing crucial roles in treatment outcomes. Technological advancements in artificial intelligence (AI) can potentially enhance orthopedic care. ChatGPT, a natural language processing technology developed by OpenAI, has shown promise in various sectors, including healthcare. ChatGPT can facilitate patient information exchange in orthopedics, provide clinical decision support, and improve patient communication and education. It can assist in differential diagnosis, suggest appropriate imaging modalities, and optimize treatment plans based on evidence-based guidelines. However, ChatGPT has limitations, such as insufficient expertise in specialized domains and a lack of contextual understanding. The application of ChatGPT in orthopedics is still evolving, with studies exploring its potential in clinical decision-making, patient education, workflow optimization, and scientific literature. The results indicate both the benefits and limitations of ChatGPT, emphasizing the need for caution, ethical considerations, and human oversight. Addressing training data quality, biases, data privacy, and accountability challenges is crucial for responsible implementation. While ChatGPT has the potential to transform orthopedic healthcare, further research and development are necessary to ensure its reliability, accuracy, and ethical use in patient care.

Indexed as

AIartificial intelligenceChatGPTclinical decision-makingorthopedicspatient education

Identifiers

PMID38026475
PMCPMC10654618

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.