The development trend of artificial intelligence in medical: A patentometric analysis

• Published in: Artificial intelligence in the life sciences Vol. 1; p. 100006
• Main Authors: Xin, Yang, Man, Wang, Yi, Zhou
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2021; Elsevier
• Subjects: Artificial intelligence; Medical; Patentometric; Social network analysis; Patentometric; Medical; Social network analysis; Artificial intelligence
• ISSN: 2667-3185; 2667-3185
• DOI: 10.1016/j.ailsci.2021.100006

Despite the burgeoning development of artificial intelligence (AI) applied in the medical field, there have been little bibliometric and collaboration network researches on the patents related to this inter-disciplinary research domain. Patentometric and Social Network Analysis (SNA) are used to conduct the characterizations of patent applications and cooperative networks, mapping a holistic landscape related to the AI-medical field. Derwent Innovation Index database (DII) is adopted as the patent data source. The results indicate that the quantity of AI-medical-related patent applications has been increasing explosively since 2011. The United States of America (US) is both the foremost country developing related technologies and the primary target of patent filing by non-residents. The hotspot of the current research include medical image recognition, computer-aided diagnosis, disease monitoring, disease prediction, bioinformatics, and drug development, etc. Low density of the assignees cooperation network implies the slight patent collaboration. Companies and academic institutions are the friskiest innovation subjects in the AI-medical field. The geographical proximity has a positive influence on the patent collaboration because co-owned patents are concentrated on the institutes in the same nation. Domestic collaboration is the major collaborative pattern. The spatial agglomeration of trans-regional patent cooperation is fairly sparse, which requires a further escalation in knowledge circulation. It has practical significance to understand the developing situation and patent cooperation network in the AI-medical field, providing a reference for future strategy planning, development, and technological marketization. [Display omitted]