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: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.

Objective To use the liquid protein combined with MALDI-TOF-MS for screening the serum differential peptides markers in lung adenocarcinoma patients and to establish the lung adenocarcinoma diag-nosed prediction model for founding the potential markers for the diagnosis of lung adenocarcinoma.Methods 37 patients with lung adenocarcinoma and 33 healthy subjects and benign lung disease which were made up in control group were collected,in the two groups the age and the sex were matched.The two groups were ran-domly divided into training group(30 cases of lung adenocarcinoma,26 cases of control)and test group(7 ca-ses of lung adenocarcinoma,7 cases of control)according to 3:1.T he differential diagnosis of lung adenocarci-noma and control group was performed by liquid chip-time-of-flight mass spectrometry and software ClinPro-Tools 3.0 to establish a prediction model of lung adenocarcinoma.The diagnostic model was validated by using serum samples from the test group to assess the diagnostic efficacy of the model.Results Nine peptide peaks with significant differences(P<0.05)were obtained by ClinProTools 3.0 software analysis.The up-regulated peaks in lung adenocarcinoma(m/z)were 8 976.5,4 469.05,4 966.78,8 925.5,4 531.05,and the down-reg-ulated m/z were 3 304.44,8 594.76,3 266.82,3 195.52.According to the genetic algorithm(GA),the lung ad-enocarcinoma diagnosis and prediction model was established.The overall recognition ability of the model was 94.49%.The model was evaluated by the test group.The results showed that the sensitivity of the model was 100.0% and the specificity was 85.7%.Conclusion Among lung adenocarcinoma patients,serum benign lung disease and healthy,there are differences in the serum peptide.T he use of differential peptide peaks to estab-lish lung adenocarcinoma diagnostic prediction model for the early diagnosis of lung adenocarcinoma provides a new method.

Objective To investigate the distribution and resistant pattern of Enterobacter cloacae to antimicrobial agents for reasonable use of antibiotics .Methods E .cloacae strains were isolated from patients from January 2009 to December 2013 .The strains were identified by VITEK‐2 Compact System of BioMerieux and tested for antimicrobial susceptibility by Kirby‐Bauer disk diffusion method .The results were analyzed .Results A total of 397 nonduplicate E .cloacae strains were isolated during 5 years ,accounting for 5 % of the total gram‐negative isolates . The strains were mainly isolated from sputum (48 .9% ) , followed by secretions (30 .5% )and urine (7 .3% ) .The percentage of E .cloacae strains resistant to all the antibiotics tested was on decline except carbapenems ,cefoxitin and amoxicillin‐clavulanic acid .Carbapenems were relatively more active against E .cloacae strains .The E .cloacae strains showed higher resistance rate toβ‐lactams .Conclusions It is necessary to strengthen the monitoring of clinical isolates to guide rational use of antimicrobial agents .

Visceral leishmaniasis (VL) is a parasitic disease ,which is still endemic in western China .An earthquake struck south-western China on May 12th ,2008 ,which affected Longnan City of Gansu Province considerably .The objective of this survey is to determine the effect of the Wenchuan earthquake on the Kala-azar epidemic in Longnan City .In this study ,VL cases were collected from 2005 to 2013 and diagnosed on positive test for anti-rK39IgG antibodies by the Kala-azar Detect rK39 dip-stick (InBios ,USA) .The incidence rates were calculated among various counties of Longnan City with SPSS 19 .0 soft-ware .The epidemiological characteristics of the disease were analyzed before and after the Wenchuan earthquake .From 2005 to 2013 ,there were 825 VL cases in Longnan City ,with an annual incidence of 3 .36/100 000 and a significantly higher incidence in males than that in females (P＜ 0 .001) .All age groups were affected .During this period ,there was an obvious upward trend from 2005 to 2008 ,and a distinct downward tendency since 2010 .The incidences of VL between 2008 and 2010 were sig-nificantly different with that in other years (P＜0 .01) .Results revealed that VL was widespread in Longnan City ,which was likely exacerbated by the earthquake in 2008 .Earthquake created diverse natural environment and social circumstances ,w hich may contribute to the spread of the VL epidemic .Together ,our data strongly suggest that the epidemic of VL should be close-ly monitored after earthquake .