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Comment
. 2021 Dec 1;274(6):e941-e942.
doi: 10.1097/SLA.0000000000004939.

Comment on "Natural Language Processing in Surgery: A Systematic Review and Meta-analysis"

Affiliations
Comment

Comment on "Natural Language Processing in Surgery: A Systematic Review and Meta-analysis"

Roi Anteby et al. Ann Surg. .
No abstract available

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Conflict of interest statement

The authors report no conflicts of interest.

Comment on

References

    1. Mellia JA, Basta MN, Toyoda Y, et al. Natural language processing in surgery: a systematic review and meta-analysis. Ann Surg 2021; 273:900–908.
    1. Sorin V, Barash Y, Konen E, et al. Deep-learning natural language processing for oncological applications. Lancet Oncol 2020; 21:1553–1556.
    1. Anteby R, Horesh N, Soffer S, et al. Deep learning visual analysis in laparoscopic surgery: a systematic review and diagnostic test accuracy meta-analysis. Surg Endosc 2021; 35:1521–1533.
    1. Gori D, Banerjee I, Chung BI, et al. Extracting patient-centered outcomes from clinical notes in electronic health records: assessment of urinary incontinence after radical prostatectomy. eGEMs 2019; 7:43.
    1. Devlin J, Chang M-W, Lee K, Toutanova K. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. 2018; Available at http://arxiv.org/abs/1810.04805 .

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