Research results from Faculty of Data Science Professor Kazumi Kubota as co-leader author were published in the International Nursing Review (Wiley), a peer-reviewed international journal published in Impact Factor (IF) 3.7. You can see the published papers from the following URL.

https://pubmed.ncbi.nlm.nih.gov/40781830

This study explores the possibility of formalizing the “tacit knowledge” that midwives have cultivated over many years of experience using AI technology (machine learning and natural language processing) and using it for clinical practice and policy planning. As a result of the analysis, it was shown that visualizing empirical knowledge can help prevent trauma and support clinical judgment, while maintaining ethical governance and privacy protection is essential.

This result is of great significance as the first step in creating a system that will contribute to improving the quality of medical care, developing human resources, and designing systems by sharing the potential knowledge of midwifery work throughout society.

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Shimonoseki City University
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