Improving accessibility of scientific research by artificial intelligence-An example for lay abstract generation
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Updated: Jul 24, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
1Department of Rehabilitation Sciences, Faculty of Health, University of Witten/Herdecke, Witten, Germany.
Abstract:
The role of scientific research in modern society is essential for driving innovation, informing policy decisions, and shaping public opinion. However, communicating scientific findings to the general public can be challenging due to the technical and complex nature of scientific research. Lay abstracts are written summaries of scientific research that are designed to be easily understandable and provide a concise and clear overview of key findings and implications. Artificial intelligence language models have the potential to generate lay abstracts that are consistent and accurate while reducing the potential for misinterpretation or bias. This study presents examples of artificial intelligence-generated lay abstracts of recently published articles, which were produced using different currently available artificial intelligence tools. The generated abstracts were of high linguistic quality and accurately represented the findings of the original articles. Adopting lay summaries can increase the visibility, impact, and transparency of scientific research, and enhance scientists' reputation among peers, while currently, available artificial intelligence models offer solutions to produce lay abstracts. However, the coherence and accuracy of artificial intelligence language models must be validated before they can be used for this purpose without restrictions.
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