Evidence map›Paper›PMID 40659532›Full record

ArticleInternational journal of spine surgery2025

Artificial Intelligence: The Prevalent Coauthor Among Early-Career Surgeons.

Franziska C S Altorfer, Giuseppe Loggia, Fedan Avrumova, Darren R Lebl

Abstract read
In one paragraph

Article in International journal of spine surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Franziska C S AltorferDepartment of Spine Surgery, Hospital for Special Surgery, New York, NY, USA.
Giuseppe LoggiaDepartment of Spine Surgery, Hospital for Special Surgery, New York, NY, USA.
Fedan AvrumovaDepartment of Spine Surgery, Hospital for Special Surgery, New York, NY, USA.
Darren R LeblDepartment of Spine Surgery, Hospital for Special Surgery, New York, NY, USA research@leblspinemd.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

designCross-sectional survey study

backgroundArtificial intelligence (AI) tools are increasingly integrated into various aspects of medicine, including medical research. However, the scope and manner in which early-career surgeons utilize AI tools in their research remain inadequately understood.

objectiveThis study aimed to investigate the frequency and specific applications of AI tools in medical research among early-career surgeons, including their perceptions, concerns, and outlook regarding AI in research.

methodsA survey comprising 25 questions was distributed among members of an international club of early-career spine surgeons (<10 years of experience). The survey assessed demographics, AI tool utilization, access to AI training resources, and perceptions of AI benefits and concerns in research.

resultsSixty early-career surgeons participated, with 86.7% reporting AI tool use in their research. ChatGPT was the most frequently utilized tool, with a usage rate of 93.1%. AI tools were primarily used for grammatical proofreading (69.6%) and rephrasing (64.3%), while 26.8% of participants used AI for statistical analysis. While 80.4% perceived improved efficiency as a key benefit, 70.0% expressed concerns about reliability. None of the participants had received formal AI training, and only 15.0% had access to AI mentors. Despite these challenges, 91.6% anticipated a positive long-term impact of AI on research.

conclusionAI tools are widely adopted among early-career surgeons for various research tasks, extending from text generation to data analysis. However, the absence of formal training and concerns regarding the reliability of AI tools underscore the necessity of training for AI integration in medical research. CLINICAL RELEVANCE: This study provides timely insights into AI adoption patterns among early-career surgeons, highlighting the urgent need for formal AI training programs to ensure responsible research practices. LEVEL OF EVIDENCE: 4:

Indexed as

AI ethicsartificial intelligenceearly-career surgeonsmedical researchresearch methodology

Identifiers

PMID40659532
PMCPMC12679427

What OpenQuestion holds

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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.