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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Critical evaluation of applications of artificial intelligence based linguistic models in Occupational Health
Mateus Lins Dos Santos1,2, Vera Nascimento Gomes Victória3
16ª Vara, Justiça Federal em Sergipe, Itabaiana, SE, Brazil.
Abstract:
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.
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