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

[摘 要] 目的：探究高迁移率族蛋白B1（HMGB1）中和抗体对肺癌LLC细胞移植瘤模型小鼠放疗联合PD-1抑制剂致放射性肺损伤的影响。方法: 实验用25只雄性C57BL/6小鼠，随机分为对照组、PD-1抑制剂组、放疗组、放疗 + PD-1抑制剂组及HMGB1中和抗体 + PD-1抑制剂 + 放疗组，每组5只。向每只动物的右腿皮下移植肺癌LLC细胞作为原发肿瘤，间日左腿皮下移植LLC细胞作为继发肿瘤。实验第28天处死动物取肺组织和移植瘤，用H-E、Masson染色观察肺组织病理变化情况，免疫组织化学法检测肺组织和移植瘤组织中CD4+和CD8+ T淋巴细胞浸润情况，酶联免疫吸附实验（ELISA）检测肺组织中TNF‐α、TGF-β和IL-6的表达。结果: 与对照或PD-1抑制剂组比较，其他3组小鼠移植瘤体积明显缩小（P < 0.01或P < 0.001），HMGB1中和抗体不能使移植瘤体积进一步缩小；与对照或PD-1抑制剂组比较，其他3组小鼠肺组织的炎症评分和胶原容积分数（CVF）均明显增加（P < 0.05、P < 0.01、P < 0.001或P < 0.000 1），HMGB1中和抗体可部分抑制放疗的不良反应（P < 0.01或P < 0.001）；与对照或PD-1抑制剂组比较，其他3组肺组织中CD4+ T淋巴细胞浸润明显增多（均P < 0.001），HMGB1中和抗体可部分抑制肺组织中CD4+ T淋巴细胞浸润（P < 0.01）；与对照或PD-1抑制剂组比较，其他3组移植瘤组织中CD4+ 、CD8+ T淋巴细胞浸润明显增加（均P < 0.001），HMGB1中和抗体不能抑制移植瘤组织中T细胞的浸润。与对照或PD-1抑制剂组比较，其他3组肺组织中IL-6表达升高，TGF-β表达下降（均P < 0.05），HMGB1中和抗体对肺组织中TNF-α、IL-6和TGF-β表达无明显影响。结论: HMGB1中和抗体不影响对移植瘤生长抑制的前提下，可能通过减少肺部炎性细胞的浸润，进而减轻肺部炎性损伤及纤维化。

[Objective]To explore the occurrence of gasdermin D(GSDMD)-mediated pyroptosis and its effect on cell proliferation,migration and tubular formation abilities of synovial vascular endothelial cells(VEC)in rheumatoid arthritis(RA).[Methods]Synovium tissues from knee joints of 22 RA patients and 18 orthopaedic arthropathies(Orth.A)patients were collected.The level of activated GSDMD-NT segment in synovium was detected by Western blot.The clinical characteristics of RA patients were compared between high and low synovial GSDMD-NT groups.The cell localization of GSDMD in RA synovium was detected by immunofluorescence staining.RA synovial fluid was added to the culture of human umbilical vein endothelial cells(HUVEC)in vitro,and the level of apoptosis and expression of pyroptosis pathway proteins were detected.The effects of GSDMD on apoptosis,proliferation,migration and tubule formation of HUVEC cells were analyzed.[Results]GSDMD expression in RA synovium was significantly higher than that in Orth.A,and more severe joint destruction and higher microvascular count score were found in RA patients with high GSDMD-NT expression.Synovial VEC had positive expression of GSDMD.Stimulation with RA synovial fluid could induce GSDMD-mediated pyroptosis in HUVEC,increased the secretion of vascular endothelial growth factor(VEGF)and their abilities of proliferation,migration and tubule formation.Knockdown of GSDMD could reverse the above effects.[Conclusion]GSDMD-mediated pyroptosis of partial synovial VEC aggravates RA joint destruction through VEGF secretion that promotes proliferation,migration and angiogenesis of the remaining VEC,which may be a new target to block neovascularization and inhibit joint destruction in RA.

We report the successful treatment of mitral regurgitation by remote robotic transcatheter edge-to-edge repair(TEER)under pure transesophageal echocardiographic guidance in a 70-year-old male patient with severe mitral regurgitation due to ischemic cardiomyopathy.The patient showed no significant improvement after coronary interventional treatment and guideline-directed medical therapy before TEER.Following a multidisciplinary discussion,a TEER procedure was indicated and performed.The procedure utilized robotic assistance guided by echocardiography,combined with 5G communication technology,to remotely operate the surgical robot in Shenzhen from Beijing.Postoperatively,the patient's mitral regurgitation was reduced to trace,symptoms were markedly improved,there were no severe complications,and the patient was discharged five days after the operation.The integration of pure echo-guided interventional technology with remote robotic operation holds significant importance for enhancing the capabilities in treating cardiovascular diseases at the primary hospitals.

This article reports a case using China's self-developed HaloStitch? system to complete a percutaneous suture-mediated patent foramen ovale closure under ultrasound guidance alone,achieving outstanding clinical outcomes.This innovative method represents a new approach to patent foramen ovale treatment and is an ideal surgical technique.

Objective To formulate the quantitative grip strength training program for application in the postoperative patients with autogenous arteriovenous internal fistula,and to evaluate its effect on the mat-uration and initial use of autogenous arteriovenous internal fistula.Methods A total of 98 patients with ce-phalic venous radial arterial anastomosis internal fistula formation surgery in Shenzhen Hospital of Southern Medical University from September 2021 to November 2022 were selected as the study subjects by the conven-ience sampling method.According to the follow-up time,they were divided into the observation group (n=41) and control group (n=42).The observation group adopted the quantitative grip strength training for function-al exercise of the limb on the side of internal fistula,while the control group adopted the conventional grip training for functional exercise of the limb on the side of internal fistula.In postoperative 8 weeks,the matura-tion rate of internal fistula,natural blood flow amount of internal fistula,internal diameter of cephalic vein,pre-pump pressure used in the initial stage of internal fistula and the incidence rate of internal fistula complica-tions were evaluated in the two groups.Results Compared with the control group,the maturation rate of in-ternal fistula in the observation group was higher (97.6％ vs. 83.3％).The inner diameter of cephalic vein and natural blood flow amount of internal fistula in the observation group were larger than those in the control group[(5.24±0.66)mm vs. (4.63±0.59)mm;(1215.38±562.99)mL/min vs. (955.75±341.94)mL/min],the pre-pump pressure used at the initial stage of internal fistula in the observation group was lower than that in the control group[(119.20±19.83)mmHg vs. (135.74±17.07)mmHg],and the differences were statistically significant (P<0.05).Conclusion The quantitative grip strength training could increase the postoperative maturity rate of patients's internal fistula,and is beneficial to the use in the initial stage of internal fistula.

Objective:To investigate the correlation between miR-137 gene polymorphism and genetic susceptibility to gestational diabetes mellitus.Methods:A total of 500 pregnant women with gestational diabetes who were admitted to Shunde Women and Childrens Hospital of Guangdong Medical University from January 2023 to September 2023 were selected as the observation group, and 500 healthy pregnant women with normal glucose metabolism and no pregnancy complications were selected as the control group. Polymerase chain reaction (PCR) was used to detect rs1625579 polymorphisms of miR-137 gene between the two groups, and the clinical data of the two groups were compared to analyze the influencing factors of the occurrence of gestational diabetes mellitus.Results:The frequencies of GT+ GG genotype and allele G at rs1625579 site of miR-137 gene in observation group were 13.20% and 7.00%, respectively, which were significantly higher than those in control group (all P<0.05). Fasting blood glucose (FPG), fasting insulin (FINS) and insulin resistance index (HOMA-IR) of miR-137 genotype GT+ GG pregnant women in the observation group were (7.92±0.81)mmol/L, (19.92±3.10)mmol/L and 6.60±1.02, respectively. It was significantly higher than genotypic TT pregnant women (all P<0.05), and islet β cell function index (HOMA-β) was significantly lower than genotypic TT pregnant women (188.84±43.34) ( P<0.05). Pre-pregnancy body mass index (BMI) and average weekly weight gain during pregnancy in the observation group were (23.81±1.92)kg/m 2 and (445.50±35.65)g, respectively, which were significantly higher than those in the control group (all P<0.05). The proportion of family history of diabetes in the observation group was 8.60%, which was significantly higher than that in the control group ( P<0.05). Logistic regression analysis showed that preconception BMI and average weekly weight gain during pregnancy were the influential factors for the occurrence of gestational diabetes (all P<0.05). Conclusions:The occurrence of gestational diabetes mellitus has no significant correlation with miR-137 gene polymorphism, but is related to pre-pregnancy BMI and average weekly weight gain during pregnancy. Compared with other miR-137 genotypes, GT+ GG patients were more likely to develop abnormal blood glucose.