The study published on ScienceDirect emphasizes the role of large language models (LLMs) as clinical decision support systems (CDSS) in enhancing medication safety across 16 clinical specialties. By leveraging advanced natural language processing capabilities, LLMs assist healthcare professionals in making informed decisions about drug prescriptions, identifying potential drug interactions, and ensuring adherence to clinical guidelines. This innovative technology not only streamlines workflows but also reduces the likelihood of medication errors, ultimately improving patient outcomes. The research underscores the transformative potential of integrating LLMs in clinical environments, highlighting their contribution to evidence-based medicine while addressing safety concerns. As healthcare continues to evolve, adopting AI-powered solutions like LLMs can significantly bolster the reliability and efficiency of clinical decision-making processes. Emphasizing these advancements positions the healthcare sector to better meet the demands of modern patient care while promoting safety and efficacy in medication management.
Keywords: large language models, clinical decision support, medication safety, artificial intelligence, healthcare innovation, patient outcomes.
