Related papers: Will Large Language Models Transform Clinical Prediction?

Will Large Language Models Transform Clinical Prediction?

URL: http://arxiv.org/abs/2505.18246v1
Date: Fri, 23 May 2025 17:02:04 GMT
Title: Will Large Language Models Transform Clinical Prediction?
Authors: Yusuf Yildiz, Goran Nenadic, Meghna Jani, David A. Jenkins,
Abstract summary: Large language models (LLMs) are attracting increasing interest in healthcare.<n>Their ability to summarise large datasets effectively, answer questions accurately, and generate synthesised text is widely recognised.
Score: 3.5700883813789472
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: Background: Large language models (LLMs) are attracting increasing interest in healthcare. Their ability to summarise large datasets effectively, answer questions accurately, and generate synthesised text is widely recognised. These capabilities are already finding applications in healthcare. Body: This commentary discusses LLMs usage in the clinical prediction context and highlight potential benefits and existing challenges. In these early stages, the focus should be on extending the methodology, specifically on validation, fairness and bias evaluation, survival analysis and development of regulations. Conclusion: We conclude that further work and domain-specific considerations need to be made for full integration into the clinical prediction workflows.

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