Evidence map›Paper›PMID 40067594›Full record

ReviewUpdates in surgery2026

Transforming plastic surgery: an innovative role of Chat GPT in plastic surgery practices.

Esmaeil Mehraeen, Niloofar Attarian, Amir Tabari, SeyedAhmad SeyedAlinaghi

Abstract readReview
PubMed Publisher
In one paragraph

Review in Updates in surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. 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

4 authors.

Esmaeil MehraeenDepartment of Health Information Technology, Khalkhal University of Medical Sciences, Khalkhal, Iran.ORCID http://orcid.org/0000-0003-4108-2973
Niloofar AttarianSchool of Medicine, Azad University of Medical Sciences, Mashhad, Iran. nil.at1997@gmail.com.
Amir TabariSchool of Medicine, Azad University of Medical Sciences, Mashhad, Iran.
SeyedAhmad SeyedAlinaghiIranian Research Center for HIV/AIDS, Iranian Institute for Reduction of High-Risk Behaviors, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The proliferation of artificial intelligence (AI) in the healthcare sector is a present reality. The potential applications of Chat GPT in medicine are currently undergoing intense examination. This article seeks to examine the innovative capabilities and applications of Chat GPT in this field, highlighting its potential to revolutionize patient care and decision-making processes. PubMed, Scopus, Embase, Google Scholar, and Web of Science were searched by conducting a keyword search to locate studies examining the application of Chat GPT in the realm of plastic and reconstructive surgery. The titles, abstracts, and conclusions of the studies were scrutinized to select those most closely aligned with the focus of our study. This investigation involved a comprehensive review of 15 relevant articles from diverse geographical regions predominantly comprising original studies alongside five review articles. This study illustrates the significant promise of integrating Chat GPT across diverse areas of plastic surgery, encompassing research, surgeon and patient education, and clinical practice. However, the incorporation of Chat GPT into plastic surgery necessitates diligent oversight and the formulation of explicit guidelines and caution is necessary.

Indexed as

Artificial IntelligencePlastic Surgery ProceduresSurgery, PlasticGenerative Artificial IntelligenceHumansArtificial intelligenceChatGPTPlastic surgery

Identifiers

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.