Leveraging artificial intelligence in neurosurgery-unveiling ChatGPT for neurosurgical discharge summaries and operative reports

被引:4
|
作者
Dubinski, Daniel [1 ]
Won, Sae-Yeon [1 ]
Trnovec, Svorad [1 ]
Behmanesh, Bedjan [1 ]
Baumgarten, Peter [2 ]
Dinc, Nazife [2 ]
Konczalla, Juergen [3 ]
Chan, Alvin [4 ]
Bernstock, Joshua D. [5 ]
Freiman, Thomas M. [1 ]
Gessler, Florian [1 ]
机构
[1] Univ Med Rostock, Dept Neurosurg, Rostock, Germany
[2] Friedrich Schiller Univ Jena, Jena Univ Hosp, Dept Neurosurg, Jena, Germany
[3] Goethe Univ Hosp, Dept Neurosurg, Frankfurt, Germany
[4] MIT, David H Koch Inst Integrated Canc Res, Cambridge, MA USA
[5] Harvard Med Sch, Dept Neurosurg, Brigham & Womens Hosp, Boston, MA USA
关键词
Artificial intelligence; AI-generated output; Computer science; Medical documentation;
D O I
10.1007/s00701-024-05908-3
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Purpose Chat generative pre-trained transformer (GPT) is a novel large pre-trained natural language processing software that can enable scientific writing amongst a litany of other features. Given this, there is a growing interest in exploring the use of ChatGPT models as a modality to facilitate/assist in the provision of clinical care. Methods We investigated the time taken for the composition of neurosurgical discharge summaries and operative reports at a major University hospital. In so doing, we compared currently employed speech recognition software (i.e., SpeaKING) vs novel ChatGPT for three distinct neurosurgical diseases: chronic subdural hematoma, spinal decompression, and craniotomy. Furthermore, factual correctness was analyzed for the abovementioned diseases. Results The composition of neurosurgical discharge summaries and operative reports with the assistance of ChatGPT leads to a statistically significant time reduction across all three diseases/report types: p < 0.001 for chronic subdural hematoma, p < 0.001 for decompression of spinal stenosis, and p < 0.001 for craniotomy and tumor resection. However, despite a high degree of factual correctness, the preparation of a surgical report for craniotomy proved to be significantly lower (p = 0.002). Conclusion ChatGPT assisted in the writing of discharge summaries and operative reports as evidenced by an impressive reduction in time spent as compared to standard speech recognition software. While promising, the optimal use cases and ethics of AI-generated medical writing remain to be fully elucidated and must be further explored in future studies.
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页数:6
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    Daniel Dubinski
    Sae-Yeon Won
    Svorad Trnovec
    Bedjan Behmanesh
    Peter Baumgarten
    Nazife Dinc
    Juergen Konczalla
    Alvin Chan
    Joshua D. Bernstock
    Thomas M. Freiman
    Florian Gessler
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  • [10] Letter to the editor concerning "Probing artificial intelligence in neurosurgical training: ChatGPT takes a neurosurgical residents written exam" by Bartoli, Aet al
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