Publication: Large Language Model in Critical Care Medicine: Opportunities and Challenges
dc.contributor.author | Hajijama, Sameera | |
dc.date.accessioned | 2024-10-08T07:25:51Z | |
dc.date.available | 2024-10-08T07:25:51Z | |
dc.date.issued | 2024 | |
dc.description.abstract | Abstract Introduction: As artificial intelligence (AI) models continue to evolve and integrate into the healthcare system, it becomes vital to understand these innovative tools to maximize their potential and anticipate the risks. A large language model (LLM) is one of the largest forms of artificial neural networks that utilize algorithmic models to process and generate a natural language text resembling the human mind from user-generated prompts. Many are familiar with the famous model ChatGPT, but models such as Google Gemini are frequently utilized, and such models have been known to demonstrate creativity and precision.1 The tools are popular due to human-like-output, widespread public availability, and ease of usability. | en_US |
dc.identifier.other | 204-2024.75 | |
dc.identifier.uri | https://repository.mbru.ac.ae/handle/1/1568 | |
dc.language.iso | en | en_US |
dc.subject | Artificial | en_US |
dc.subject | Artificial intelligence | en_US |
dc.subject | Artificial neural network | en_US |
dc.subject | Critical care medicine | en_US |
dc.subject | Healthcare | en_US |
dc.subject | Intelligence. | en_US |
dc.title | Large Language Model in Critical Care Medicine: Opportunities and Challenges | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | en_US |