| Summary: | The article discusses the evolving landscape of laboratory medicine, focusing on the integration of refined statistical methods and artificial intelligence (AI) systems to enhance data processing and interpretation. It highlights seven articles that explore sustainable reference intervals (RIs) and clinical decision limits (CDLs), emphasizing the importance of understanding these concepts for effective clinical action. The discussion includes advancements in statistical tools, the role of machine learning in reference interval estimation, and the potential of large language models (LLMs) in therapeutic drug monitoring reporting. Additionally, it addresses the need for AI literacy among laboratory professionals, particularly in light of the EU AI Act, which mandates training in AI systems. Overall, the article underscores the dual responsibility of utilizing advanced tools while maintaining a deep understanding of their implications in clinical practice.
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