2024

Conférence

-

Large Language Models (LLMs) are being increasingly explored and used in healthcare for their potential applications. These models show the capacity to impact clinical care, research, and medical education significantly. In this research, we shed light on the transformative potential of LLMs in reshaping the healthcare landscape, emphasizing their role in enhancing patient care, improving decision-making processes, and advancing medical research. While the application of LLMs in healthcare presents immense opportunities, this research, also, addresses critical challenges and limitations. Concerns regarding the accuracy, reliability, and ethical implications of LLMs in medical contexts are highlighted, emphasizing the need for continuous monitoring and evaluation to ensure patient safety and data privacy. By exploring the opportunities and challenges associated with LLMs in healthcare, this study contributes to a deeper understanding of the implications and future directions of this technology in the healthcare sector.

@inproceedings{DBLP:conf/codit/Rezgui24,
  author       = {Kalthoum Rezgui},
  title        = {Large Language Models for Healthcare: Applications, Models, Datasets,
                  and Challenges},
  booktitle    = {10th International Conference on Control, Decision and Information
                  Technologies, CoDIT 2024, Vallette, Malta, July 1-4, 2024},
  pages        = {2366--2371},
  publisher    = {{IEEE}},
  year         = {2024},
  url          = {https://doi.org/10.1109/CoDIT62066.2024.10708253},
  doi          = {10.1109/CODIT62066.2024.10708253},
  timestamp    = {Tue, 12 Nov 2024 15:37:11 +0100},
  biburl       = {https://dblp.org/rec/conf/codit/Rezgui24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}