Stellenwert von Natural Language Processing und chatbasierten Generative Language Models

BACKGROUND: Natural language processing (NLP) has experienced significant growth in recent years and shows potential for broad impacts in scientific research and clinical practice.

OBJECTIVE: This study comprises an exploration of the role of NLP in scientific research and its subsequent effects on traditional publication practices, as well as an evaluation of the opportunities and challenges offered by large language models (LLM) and a reflection on necessary paradigm shifts in research culture.

MATERIALS AND METHODS: Current LLMs, such as ChatGPT, and their potential applications were compared and assessed. An analysis of the literature and case studies on the integration of LLMs into scientific and clinical practice was conducted.

RESULTS AND CONCLUSION: LLMs provide enhanced access to and processing capabilities of text-based information and represent a vast potential for (medical) research as well as daily clinical practice. Chat-based LLMs enable efficient completion of often time-consuming tasks, but due to their tendency for hallucinations, have a significant limitation. Current developments require critical examination and a paradigm shift to fully exploit the benefits of LLMs and minimize potential risks.