The objective of this study is to map the global scientific competitive landscape in the field of artificial intelligence (AI) medical devices using scientific data. A bibliometric analysis was conducted using the Web of Science Core Collection to examine global research trends in AI-based medical devices. As of the end of 2023, a total of 55 147 relevant publications were identified worldwide, with 76.6% published between 2018 and 2024. Research in this field has primarily focused on AI-assisted medical image and physiological signal analysis. At the national level, China (17 991 publications) and the United States (14 032 publications) lead in output. China has shown a rapid increase in publication volume, with its 2023 output exceeding twice that of the U.S.; however, the U.S. maintains a higher average citation per paper (China: 16.29; U.S.: 35.99). At the institutional level, seven Chinese institutions and three U.S. institutions rank among the global top ten in terms of publication volume. At the researcher level, prominent contributors include Acharya U Rajendra, Rueckert Daniel and Tian Jie, who have extensively explored AI-assisted medical imaging. Some researchers have specialized in specific imaging applications, such as Yang Xiaofeng (AI-assisted precision radiotherapy for tumors) and Shen Dinggang (brain imaging analysis). Others, including Gao Xiaorong and Ming Dong, focus on AI-assisted physiological signal analysis. The results confirm the rapid global development of AI in the medical device field, with "AI + imaging" emerging as the most mature direction. China and the U.S. maintain absolute leadership in this area-China slightly leads in publication volume, while the U.S., having started earlier, demonstrates higher research quality. Both countries host a large number of active research teams in this domain.
Artificial Intelligence ; Bibliometrics ; Humans ; China ; Equipment and Supplies ; United States ; Biomedical Research

The emergence of new-generation artificial intelligence technology has brought numerous innovations to the healthcare field, including telemedicine and intelligent care. However, the artificial intelligent medical device sector still faces significant challenges, such as data privacy protection and algorithm reliability. This study, based on invention patent analysis, revealed the technological innovation trends in the field of artificial intelligent medical devices from aspects such as patent application time trends, hot topics, regional distribution, and innovation players. The results showed that global invention patent applications had remained active, with technological innovations primarily focused on medical image processing, physiological signal processing, surgical robots, brain-computer interfaces, and intelligent physiological parameter monitoring technologies. The United States and China led the world in the number of invention patent applications. Major international medical device giants, such as Philips, Siemens, General Electric, and Medtronic, were at the forefront of global technological innovation, with significant advantages in patent application volumes and international market presence. Chinese universities and research institutes, such as Zhejiang University, Tianjin University, and the Shenzhen Institute of Advanced Technology, had demonstrated notable technological innovation, with a relatively high number of patent applications. However, their overseas market expansion remained limited. This study provides a comprehensive overview of the technological innovation trends in the artificial intelligent medical device field and offers valuable information support for industry development from an informatics perspective.
Artificial Intelligence ; Patents as Topic ; Humans ; Inventions ; China ; Brain-Computer Interfaces ; Telemedicine ; Equipment and Supplies ; Robotics ; Algorithms

The rapid development of artificial intelligence technology is driving profound changes in medical practice, particularly in the field of medical device application. Based on data from the U.S. clinical trials registry, this study analyzes the global registration landscape of clinical trials involving artificial intelligence-based medical devices, aiming to provide a reference for their clinical research and application. A total of 2 494 clinical trials related to artificial intelligence medical devices have been registered worldwide, with participation from 66 countries or regions. The United States leads with 908 trials, while for other countries or regions, including China, each has fewer than 300 trials. Germany, the United States, and Belgium serve as central hubs for international collaboration. Among the sponsors, 63.96% are universities or hospitals, 22.36% are enterprises, and the remainder includes individuals, government agencies and others. Of all trials, 79.99% are interventional studies, 94.67% place no restrictions on participant gender, and 69.69% exclude children. The targeted diseases are primarily neurological and mental disorders. This study systematically reveals the global distribution characteristics and research trends of artificial intelligence medical device clinical trials, offering valuable data support and practical insights for advancing international collaboration, resource allocation, and policy development in this field.
Artificial Intelligence ; Humans ; Clinical Trials as Topic/statistics & numerical data* ; Equipment and Supplies ; Registries ; United States

In recent years, the research on artificial intelligence medical devices has risen markedly along with the expanding application scenarios, exhibiting prominent interdisciplinary characteristics. From 2000 to 2024, the variety of research in artificial intelligence medical devices has significantly increased, while the balance of disciplines has slightly declined, and Simpson's diversity index has continuously increased. Medicine and biology are the main research themes and supportive disciplines in this field. Knowledge from computer science, engineering technology, and mathematics is widely involved and shows an upward trend, while content from the humanities and social sciences is less involved in the research. Compared to the United States and the United Kingdom, China has relatively less biological and chemical knowledge content in the research of this field, but more content related to computer science, engineering technology and material science is involved. This study analyzes the current state and trends of interdisciplinary on artificial intelligence medical devices from the perspective of macro-categories of disciplines, aiming to provide references for research planning, talent training and interdisciplinary cooperation in the field.
Artificial Intelligence ; Humans ; Equipment and Supplies ; Interdisciplinary Research

Objective To explore the technology frontiers for neuroblastoma treatment from the perspective of patent citation network. Methods Through patent analysis for neuroblastoma treatment, highly cited patents and highly cited papers in the citation network were taken as the research objects. The title and abstract of the citing patents were analyzed by text clustering to identify the technology frontiers. Through social network analysis, the core patents were identified from the indices of degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Results A total of 6240 patent applications for neuroblastoma treatment were found, including 71304 patent citations and 88698 journal-article citations. Four technology frontiers were identified based on patent citation network, namely, drug target, drug design, tumor-indication expansion, and gene-expression regulation. Three technology frontiers were identified based on journal-article citation network. They were drug target, drug design, and tumor-indication expansion. Conclusion The development of technology for neuroblastoma treatment continues to be active. Drug target and drug design are the most important technology frontiers. This study could provide certain reference for neuroblastoma treatment from the perspective of information science.

This research analyzed Chinese emergency approval policies and practices of medical devices at the local level under the circumstance of COVID-19 disease. The legal basis and administrative system were clarified, the implementation and characteristics of emergency approval policies were investigated, the products information including total approved number, product type and license's validity period were counted. Advices as enhancing the standardization of emergency approval system, strengthening registration guidance and optimize information disclose and management were provided.
COVID-19 ; Device Approval ; Humans ; Policy ; SARS-CoV-2

Objective:By building a COVID-19 related scientific research progress monitoring system, to mitigate the information needs of different stakeholders such as government decision-makers, enterprises and scientific research institutions, provide reference for global scientific research progress monitoring for possible public health emergencies in the future.Methods:Literature review and expert consultation were adopted to systematically sort out the data sources of journal papers, preprints and other scientific papers, formed their respective monitoring catalogs and determined the tracking path.Results:COVID-19-related papers mainly include journal papers and preprints. The data source monitoring range of journal papers includes the official websites of top journals in biomedical and natural sciences, the database Web of Science and Science Direct, and the monitoring scope of the preprint platform includes medRxiv, bioRxiv, and SSRN, etc. In addition, the virological websites virological and nextstrain should also be monitored.Conclusions:COVID-19-related scientific research progress monitoring system can be used for daily monitoring to provide support for decision-making and deployment of prevention and control work.

Atrial fibrillation is the most common persistent arrhythmia in the clinic. It affects a wide range of populations with high incidence, morbidity and mortality. Clinical studies have shown that ablation is one of the best means for the treatment of atrial fibrillation. However, after receiving ablation, some patients may experience atrial tachycardia and thus feel even deteriorated feelings. Understanding the predicting factors, electrophysiological mechanisms, and differential diagnosis and treatment strategies for post-ablation atrial tachycardia is essential for reducing the incidence and for the management of post-ablation atrial tachycardia. Therefore, we summarize the research progress of the above-mentioned aspects, and correspondingly proposes further research directions.
Atrial Fibrillation ; Catheter Ablation ; Humans ; Tachycardia, Supraventricular/surgery* ; Treatment Outcome

OBJECTIVE: In this study,computational modelling was used to study whether different conduction pathways have impact on the AF initiation and maintenance based on a human atrial model. METHODS: MRI images from one patient who has atrial fibrillation were used to reconstruct the human atrial anatomical model.The number of MRI images was 112.In order to study the effect of different conduction pathways to AF,4 different atrial models were generated in this study,which were biatrial conduction via only LFO;biatrial conduction via only CS;biatrial conduction via both LFO and CS;model without biatrial conduction. RESULTS: In the case of biatrial conduction simulation via only LFO,the same re-entries were induced as in the LFO and CS case.But for the two cases of only CS conduction and both LFO and CS cannot conduct electricity,one stimulus site induced unsustained re-entry which only lasted for 2 cycles,and then terminated.The other two sites induced the same re-entries as in the previously described two cases,which were biatrial conduction simulation via both LFO and CS and only LFO. CONCLUSIONS Our simulation showed that these conduction pathways played a minor role in the re-entry initiation and maintenance,the possible explanation is that all the re-entries induced in our simulation is local drivers and maintained by fibrosis.
Atrial Fibrillation ; Catheter Ablation ; instrumentation ; Heart Atria ; Heart Rate ; Humans

Objective To review the "Twelfth Five-Year Plan" and provide the outlook of the innovation system of Chinese medical science and technology in "Thirteenth Five-Year Plan".Methods This article mainly investigates the layout and results regarding innovation system of Chinese medical science and technology in "Twelfth Five-Year Plan" and the "Thirteenth Five-Year Plan" respectively.Results The layout of the "Twelfth Five-Year Plan" in medical technology field has provide guarantees for promoting the construction of healthy China.Meanwhile,Chinese innovation abilities in this field has been improved.Additionally,technology and equipment in China have been upgraded.However,there are still some problems,such as the lack of original research innovation capacity and urgency in the task of product quality upgrading etc.Since the "Thirteenth Five-Year Plan" is considered as the decisive stage in the process of building Chinese well-off society,it is necessary to increase the layout and investment in terms of innovation system of Chinese medical science and technology.Conclusions On the basis of "Twelfth Five-Year Plan","Thirteenth Five-Year Plan" will grasp the direction of technological progress of medical industry,and continue to promote innovation as well as provide support for improving the abilities of research and development,which could provide an inexhaustible driving force of medical technique innovation for China.