Die Rolle von Large Language Modellen in der wissenschaftlichen Recherche

Background: Large language models (LLMs) are increasingly being incorporated in scientific research, transforming the landscape across disciplines. Their potential spans various stages of the research process - from automating literature reviews and generating research questions to analyzing complex data sets and synthesizing or evaluating manuscripts. However, their implementation presents challenges, especially for researchers with limited experience using AI. Materials and Methods: This review describes the potential of LLMs to support and enhance systematic literature searches in scientific research. It analyzes their capabilities and addresses practical and ethical challenges, particularly those concerning scientific integrity, transparency, and reproducibility. Conclusion: Combining LLMs with human expertise offers a promising avenue to accelerate innovation, drive scientific discovery, and ultimately improve healthcare outcomes. Nevertheless, responsible and informed use is essential to maintain rigorous, ethical, and trustworthy scientific practices. Key Points: · LLMs can accelerate systematic literature searches through automation. · Self-hosted models offer better control, data protection, and domain-specific customization options. · Ethical challenges require transparency, quality assurance, and responsible use of AI. Citation Format: · Lindner T, Weber MA, Manzke M. The Role of Large Language Models in Scientific Research. Rofo 2026; DOI 10.1055/a-2868-7797.