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<p>This review aimed to investigate the role of large language models (LLMs) in clinical decision support, patient counseling, and patient education in the management of urolithiasis. Eleven eligible studies were assessed following a comprehensive search of the Scopus and Web of Science databases. In the realm of clinical decision support, large language models (LLMs), particularly ChatGPT-4, have shown efficacy in areas such as the diagnosis of urolithiasis and initial treatment planning. An evaluation of the models’ adherence to the European Association of Urology guidelines revealed that ChatGPT and Perplexity outperformed Bard. For patient counseling, Bing AI exhibited a robust capacity to deliver resource-based information. The studies have yielded conflicting results regarding ChatGPT versions’ ability to empathize. In the context of patient education, models such as Claude-3 and ChatGPT-4 have demonstrated the capability to provide accurate and comprehensible answers to patient questions. However, it was noted that the quality of information is occasionally conveyed using complex language. LLMs have considerable potential as assistive tools in the management of urolithiasis; however, their limitations necessitate expert supervision, especially in complex cases. In the future, it is anticipated that these limitations will be mitigated through improved training and integration of these models into clinical practice. Consequently, LLMs should be employed as auxiliary tools rather than primary instruments in clinical decision-making.</p>

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What is the role of large language models in the management of urolithiasis?: a review

  • 期刊论文

  • 发表日期：

    2025年5月15日

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  • Tunahan Ates,
  • Nezih Tamkac,
  • Ibrahim Halil Sukur,
  • Fesih Ok

摘要

This review aimed to investigate the role of large language models (LLMs) in clinical decision support, patient counseling, and patient education in the management of urolithiasis. Eleven eligible studies were assessed following a comprehensive search of the Scopus and Web of Science databases. In the realm of clinical decision support, large language models (LLMs), particularly ChatGPT-4, have shown efficacy in areas such as the diagnosis of urolithiasis and initial treatment planning. An evaluation of the models’ adherence to the European Association of Urology guidelines revealed that ChatGPT and Perplexity outperformed Bard. For patient counseling, Bing AI exhibited a robust capacity to deliver resource-based information. The studies have yielded conflicting results regarding ChatGPT versions’ ability to empathize. In the context of patient education, models such as Claude-3 and ChatGPT-4 have demonstrated the capability to provide accurate and comprehensible answers to patient questions. However, it was noted that the quality of information is occasionally conveyed using complex language. LLMs have considerable potential as assistive tools in the management of urolithiasis; however, their limitations necessitate expert supervision, especially in complex cases. In the future, it is anticipated that these limitations will be mitigated through improved training and integration of these models into clinical practice. Consequently, LLMs should be employed as auxiliary tools rather than primary instruments in clinical decision-making.