Abstract
Artificial intelligence has proven to be a valuable tool in supporting the medical sector. The integration of artificial intelligence and medicine can lead to more timely and accurate diagnoses, analyze responses to medications, and provide personalized treatment suggestions for patients. Additionally, it can streamline administrative processes, allowing medical professionals to focus more on direct patient care. Concerning this last aspect, the role of Large Language Models has become crucial to provide solutions that can mimic the behavior of a human operator and reduce the human-machine distancing. Large language models can respond to free-text queries without being specifically trained in the task in question, causing excitement and concern about their use in healthcare, especially when these responses are related to diagnoses or treatments. The objective of this work is to analyze the literature from a quantitative point of view and thoroughly understand what aspects the research has focused on up to this point, with the perspective of identify the most discussed topics and the current state of research.
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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Ruga, T. (2024). Unveiling The Role of Large Language Models in Healthcare. In: Roy, S., Sinwar, D., Dey, N., Perumal, T., R. S. Tavares, J.M. (eds) Innovations in Computational Intelligence and Computer Vision. ICICV 2024. Lecture Notes in Networks and Systems, vol 1117. Springer, Singapore. https://doi.org/10.1007/978-981-97-6992-6_2
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DOI: https://doi.org/10.1007/978-981-97-6992-6_2
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