Application of AI-assisted methodology to evaluate diet and ingredient formulations for rodent models in nutrition and health research

Abstract

The use of Artificial Intelligence (AI) for peer review is gaining interest by journals and editorial boards because of the length of time required for the scientific peer review process and large numbers of new submissions. The application of AI using a large language model (LLM) like OpenAI’s ChatGPT is a valid, rapid means to search published articles that examine diets in rodent studies. The information gathered can be used to evaluate rodent diets and nutrients during peer review or in developing studies and preparing appropriate experimental designs for future nutrition and biomedical research with rodents. However, it is vital that AI be used only to supplement and assist the human process of peer review and the final decision for publication. The use of ChatGPT has great potential to improve scientific peer review and assist researchers in developing experimental designs for nutrition research. The target of our AI application is improving understanding of why dietary and ingredient effects impact the interpretation of findings in metabolism, biochemistry, molecular and gene expression, physiology, health, and disease research in rodents. AI application with LLM validating diet approaches used in rodent studies can complement the human peer review process of scientific journals.