Evidence map›Paper›PMID 40788545›Full record

ArticleAesthetic plastic surgery2026

A Comparative Study on the Use of DeepSeek-R1 and ChatGPT-4.5 in Different Aspects of Plastic Surgery.

Rizwan Ali, Lishuai Shi, Haiyan Cui

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Aesthetic plastic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

3 authors.

Rizwan Ali *Department of Plastic and Cosmetic Surgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
Lishuai Shi *Department of Plastic and Cosmetic Surgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
Haiyan CuiDepartment of Plastic and Cosmetic Surgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200092, China. u2beauty1@sina.com.ORCID 0000-0002-0879-2415

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) has the potential to enhance medical practice, but its application in plastic surgery remains underexplored. DeepSeek-R1 and ChatGPT-4.5 are AI models that can assist with clinical tasks, but their performance in plastic surgery-related queries needs evaluation. This study compares the two models in providing clinically relevant, detailed, and accurate responses.

objectiveThe objective of this study is to evaluate and compare the performance of DeepSeek-R1 and ChatGPT-4.5 across 10 plastic surgery-related tasks, focusing on accuracy, detail, and clinical relevance.

methodsThis comparative evaluation was conducted by having two senior plastic surgeons review the AI-generated responses for each task. The responses were rated on a 1-10 scale based on their accuracy, completeness, and clinical relevance. The tasks involved both general knowledge questions and more complex, clinically relevant tasks such as medical history notes and hospital admission/discharge slips. After scoring, the mean and standard deviation (SD) were calculated for each model to evaluate their overall performance and consistency.

resultsThe results revealed that DeepSeek-R1 consistently outperformed ChatGPT-4.5 across all tasks, with higher average scores for both evaluators. DeepSeek-R1 excelled in tasks requiring high clinical detail, comprehensive explanations, and professional-level accuracy, particularly in tasks involving botulinum toxin, medical documentation, and novel research topics. In contrast, ChatGPT-4.5 was rated higher for tasks requiring concise responses, providing accurate but less detailed overviews. The mean scores for DeepSeek-R1 were significantly higher, with lower standard deviations, indicating greater consistency in its responses. ChatGPT-4.5, though performing well for general inquiries, showed more variability and scored lower in complex clinical tasks.

conclusionDeepSeek-R1 is better suited for tasks needing clinical detail and professional-level accuracy, while ChatGPT-4.5 excels in providing quick, concise responses. Both models show promise in supporting plastic surgery practice and education, but should complement, not replace, human expertise. LEVEL OF EVIDENCE V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Indexed as

Artificial IntelligenceClinical CompetencePlastic Surgery ProceduresSurgery, PlasticFemaleGenerative Artificial IntelligenceHumansMaleAI in healthcareArtificial intelligenceBotulinum toxinChatGPT-4.5Clinical decision supportDeepSeek-R1Medical documentationPlastic surgery

Identifiers

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Registered trials

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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.