在医院出院单上使用自然语言处理来监测手术部位的感染:在教学医院进行回访研究。

Q3 Medicine

Recenti progressi in medicina Pub Date : 2025-10-01 DOI:10.1701/4573.45800

Nunzio Zotti, Guglielmo Arzilli, Francesco Baglivo, Luigi De Angelis, Andrea Porretta, Caterina Rizzo

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引用次数: 0

摘要

一种基于NLP和机器学习的人工智能系统已经开发出来，可以从出院信中识别手术部位感染（ssi）。经过先进的预处理和不平衡处理，BERT-FT达到了最佳性能（F1=0.79），优于TF-IDF和W2V。大型语言模型（llm）显示出局限性。该系统可以支持半自动SSI监视，具有翻译、提示和基础设施优化的前景。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Sorveglianza delle infezioni del sito chirurgico tramite applicazione di natural language processing su lettere di dimissione ospedaliera: studio retrospettivo presso un ospedale universitario.

An AI system based on NLP and machine learning has been developed to identify surgical site infections (SSIs) from hospital discharge letters. After advanced pre-processing and imbalance handling, BERT-FT achieved the best performance (F1=0.79), outperforming TF-IDF and W2V. Large language models (LLMs) showed limitations. The system could support semi-automatic SSI surveillance, with prospects for optimisation in translations, prompts, and infrastructure.

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来源期刊

Recenti progressi in medicina Medicine-Medicine (all)

CiteScore

0.90

自引率

0.00%

发文量

143

期刊介绍： Giunta ormai al sessantesimo anno, Recenti Progressi in Medicina continua a costituire un sicuro punto di riferimento ed uno strumento di lavoro fondamentale per l"ampliamento dell"orizzonte culturale del medico italiano. Recenti Progressi in Medicina è una rivista di medicina interna. Ciò significa il recupero di un"ottica globale e integrata, idonea ad evitare sia i particolarismi della informazione specialistica sia la frammentazione di quella generalista.