Robert Kaczmarczyk, Theresa Isabelle Wilhelm, Jonas Roos, Ron Martin
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引用次数: 0
Abstract
Background: As the digital health landscape continues to evolve, analyzing the progress and direction of the field can yield valuable insights. The Journal of Medical Internet Research (JMIR) has been at the forefront of disseminating digital health research since 1999. A comprehensive network analysis of JMIR publications can help illuminate the evolution and trends in digital medicine over the past 25 years.
Objective: This study aims to conduct a detailed network analysis of JMIR's publications to uncover the growth patterns, dominant themes, and potential future trajectories in digital health research.
Methods: We retrieved 8068 JMIR papers from PubMed using the Biopython library. Keyword metrics were assessed using accuracy, recall, and F1-scores to evaluate the effectiveness of keyword identification from Claude 3 Opus and Gemini 1.5 Pro in addition to 2 conventional natural language processing methods using key bidirectional encoder representations from transformers. Future trends for 2024-2026 were predicted using Claude 3 Opus, Google's Time Series Foundation Model, autoregressive integrated moving average, exponential smoothing, and Prophet. Network visualization techniques were used to represent and analyze the complex relationships between collaborating countries, paper types, and keyword co-occurrence.
Results: JMIR's publication volume showed consistent growth, with a peak in 2020. The United States dominated country contributions, with China showing a notable increase in recent years. Keyword analysis from 1999 to 2023 showed significant thematic shifts, from an early internet and digital health focus to the dominance of COVID-19 and advanced technologies such as machine learning. Predictions for 2024-2026 suggest an increased focus on artificial intelligence, digital health, and mental health.
Conclusions: Network analysis of JMIR publications provides a macroscopic view of the evolution of the digital health field. The journal's trajectory reflects broader technological advances and shifting research priorities, including the impact of the COVID-19 pandemic. The predicted trends underscore the growing importance of computational technology in future health care research and practice. The findings from JMIR provide a glimpse into the future of digital medicine, suggesting a robust integration of artificial intelligence and continued emphasis on mental health in the postpandemic era.
解码数字脉搏:通过《医学互联网研究杂志》对数字健康研究 25 年的文献计量学分析》(Decoding the Digital Pulse: Bibliometric Analysis of 25 Years in Digital Health Research Through the Journal of Medical Internet Research)。
背景:随着数字健康领域的不断发展,对该领域的进展和方向进行分析可以获得有价值的见解。自 1999 年以来,《医学互联网研究杂志》(JMIR)一直走在传播数字医疗研究的前沿。对 JMIR 出版物进行全面的网络分析有助于揭示过去 25 年数字医学的发展和趋势:本研究旨在对 JMIR 的出版物进行详细的网络分析,以揭示数字健康研究的增长模式、主导主题和潜在的未来轨迹:我们使用 Biopython 库从 PubMed 检索了 8068 篇 JMIR 论文。使用准确率、召回率和 F1 分数对关键词指标进行评估,以评价 Claude 3 Opus 和 Gemini 1.5 Pro 的关键词识别效果,以及使用转换器关键双向编码器表示的两种传统自然语言处理方法的效果。使用 Claude 3 Opus、谷歌时间序列基础模型、自回归综合移动平均法、指数平滑法和先知预测了 2024-2026 年的未来趋势。使用网络可视化技术来表示和分析合作国家、论文类型和关键词共同出现之间的复杂关系:结果:JMIR 的发表量呈现持续增长态势,并在 2020 年达到顶峰。美国的贡献占主导地位,而中国近年来的贡献显著增加。从 1999 年到 2023 年的关键词分析表明,主题发生了显著变化,从早期的互联网和数字健康为主,到 COVID-19 和机器学习等先进技术占主导地位。对2024-2026年的预测表明,人工智能、数字健康和心理健康将受到更多关注:对 JMIR 出版物的网络分析提供了数字健康领域发展的宏观视角。该期刊的发展轨迹反映了更广泛的技术进步和研究重点的转移,包括 COVID-19 大流行病的影响。预测的趋势强调了计算技术在未来医疗保健研究和实践中日益增长的重要性。JMIR 的研究结果让我们看到了数字医学的未来,表明在后大流行时代,人工智能将得到有力的整合,心理健康将继续受到重视。
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.