Knowledge Mapping of Medical AI Ethics: A Cross-Country Comparative Analysis

Abstract

The widespread application of artificial intelligence(AI) technology in medicine has brought unprecedented opportunities for healthcare service and health management. However, ethical issues such as data privacy, fairness, transparency, and algorithmic bias have become more prominent, which attract attention of both the academia and the public. This study systematically analyzes the current status, hotspots, and trends of medical AI ethics research through a combination of bibliometrics and knowledge mapping analysis, while comparing Chinese and international research. The findings show that research in medical AI ethics has been increasing annually, with academic research networks gradually forming, although Chinese research lags behind English-language research in both quantity and growth rate. Chinese and international research share similar network structure characteristics, but neither has formed a close-knit academic community yet. In terms of research characteristics, international research is led by interdisciplinary departments, showing significant cross-disciplinary collaboration, while Chinese research is primarily conducted by medical schools and their affiliated hospitals, with more emphasis on inter-departmental collaboration within institutions. Although both focus on core issues such as privacy protection and data security, international research emphasizes the integration of technology and ethics, while Chinese research focuses more on developing localized ethical theoretical frameworks. The research results provide important references for promoting the development of medical AI ethics research.