Dos Santos Mateus Lins, Victória Vera Nascimento Gomes
6ª Vara, Justiça Federal em Sergipe, Itabaiana, SE, Brazil.
9ª Vara, Justiça Federal em Sergipe, Propriá, SE, Brazil.
Rev Bras Med Trab. 2024 Aug 5;22(1):e20231241. doi: 10.47626/1679-4435-2023-1241. eCollection 2024 Jan-Mar.
This article explores the impact and potential applications of large language models in Occupational Medicine. Large language models have the ability to provide support for medical decision-making, patient screening, summarization and creation of technical, scientific, and legal documents, training and education for doctors and occupational health teams, as well as patient education, potentially leading to lower costs, reduced time expenditure, and a lower incidence of human errors. Despite promising results and a wide range of applications, large language models also have significant limitations in terms of their accuracy, the risk of generating false information, and incorrect recommendations. Various ethical aspects that have not been well elucidated by the medical and academic communities should also be considered, and the lack of regulation by government entities can create areas of legal uncertainty regarding their use in Occupational Medicine and in the legal environment. Significant future improvements can be expected in these models in the coming years, and further studies on the applications of large language models in Occupational Medicine should be encouraged.
本文探讨了大语言模型在职业医学中的影响和潜在应用。大语言模型有能力为医疗决策、患者筛查、技术、科学和法律文件的总结与创作、医生和职业健康团队的培训与教育以及患者教育提供支持，这可能带来成本降低、时间支出减少和人为错误发生率降低的结果。尽管取得了令人鼓舞的成果且应用广泛，但大语言模型在准确性、生成虚假信息的风险和错误推荐方面也存在重大局限性。医学和学术界尚未充分阐明的各种伦理问题也应予以考虑，而且政府实体缺乏监管可能会在职业医学和法律环境中使用大语言模型方面造成法律不确定性领域。预计未来几年这些模型会有显著改进，应鼓励对大语言模型在职业医学中的应用进行进一步研究。
