Applications of Explainable Artificial Intelligent Algorithms to Medicine: A Bibliographic Study

In recent years, Explainable Artificial Intelligent (XAI) algorithms have been widely applied and deeply studied in the field of medicine. Based on the bibliometric method, this paper summarizes and analyses 315 non-repetitive related literature retrieved from the literature databases of Scopus and Web of Science (WOS). Developing trends, key authors, contributed countries, journals, references, and keywords are explored. Based on the method of text mining, representative articles, and their core opinions are qualitatively analyzed. Methods are clustered, applications, strengths, and drawbacks are discussed, and issues and future directions are exhibited. Findings show that applications of the interpretable algorithm to the medical field have vital potential clinical value. Medical diagnosis based on computer vision with an explainable mechanism is aimed at breaking the trust between artificial intelligence and medicine disciplines. In addition, cooperative research and talent training in this interdisciplinary area are also worthy of attention in the future. Thus, a reference significance for XAI applied to the medical field is contributed by this study.