Zeye Liu, Ziping Li, Hong Jiang, Guangyu Pan, Wenchao Li, Fengwen Zhang, Wen-Bin Ou-Yang, Shouzheng Wang, Cheng Wang, Xuanqi An, Anlin Dai, Ruibing Xia, Yakun Li, Xiaochun Sun, Yi Shi, Chengliang Yin, Xiang-Bin Pan
{"title":"分析和预测心血管研究热点、趋势和交叉学科。","authors":"Zeye Liu, Ziping Li, Hong Jiang, Guangyu Pan, Wenchao Li, Fengwen Zhang, Wen-Bin Ou-Yang, Shouzheng Wang, Cheng Wang, Xuanqi An, Anlin Dai, Ruibing Xia, Yakun Li, Xiaochun Sun, Yi Shi, Chengliang Yin, Xiang-Bin Pan","doi":"10.1136/heartjnl-2025-325877","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Comprehensive data and analyses on cardiovascular research could clarify recent research trends for the academic community and facilitate policy development. We examined publications and reference data to identify research topics, trends and interdisciplinarity for cardiovascular disease (CVD).</p><p><strong>Methods: </strong>We extracted and clustered text fragments from the titles and abstracts of 2 512 445 publications using artificial intelligence techniques, including natural language processing (NLP) for semantic analysis. Cardiovascular experts identified topics and document clusters based on the output of those semiautomatic methods. We also applied machine learning algorithms to predict the trends over the next 5 years in each field. We examined the crossover between the two cluster groups using citation relationships in the documents.</p><p><strong>Results: </strong>Research in clinical studies showed the most notable increase; that was followed by research in population and basic studies. The research hotspots were minimally invasive treatments for valve disease, circulatory haemodynamics, and prevention and control of hypertension. The fastest-growing topics were health monitoring, evidence-based medicine and immunotherapy. We found extensive crossover relationships among document clusters for the periods of 2017-2018 and 2020-2021.</p><p><strong>Conclusions: </strong>This study provides valuable insights into the research hotspots for cardiovascular research, including an increasing emphasis on early disease detection and prevention, exploration of minimally invasive treatments and assessment of risk factors. The research landscape demonstrates signs of interdisciplinarity and integration as reflected in citation relationships. These findings suggest practical implications for optimising resource allocation in healthcare systems, guiding clinical guideline updates and informing policy-making to prioritise high-impact research areas aligned with evolving CVD challenges. Given the evolving global burden of CVD, continuous research and innovation are imperative, with interdisciplinary collaboration assuming a pivotal role in advancing scientific knowledge.</p>","PeriodicalId":12835,"journal":{"name":"Heart","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis and prediction of cardiovascular research hotspots, trends and interdisciplinarity.\",\"authors\":\"Zeye Liu, Ziping Li, Hong Jiang, Guangyu Pan, Wenchao Li, Fengwen Zhang, Wen-Bin Ou-Yang, Shouzheng Wang, Cheng Wang, Xuanqi An, Anlin Dai, Ruibing Xia, Yakun Li, Xiaochun Sun, Yi Shi, Chengliang Yin, Xiang-Bin Pan\",\"doi\":\"10.1136/heartjnl-2025-325877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Comprehensive data and analyses on cardiovascular research could clarify recent research trends for the academic community and facilitate policy development. We examined publications and reference data to identify research topics, trends and interdisciplinarity for cardiovascular disease (CVD).</p><p><strong>Methods: </strong>We extracted and clustered text fragments from the titles and abstracts of 2 512 445 publications using artificial intelligence techniques, including natural language processing (NLP) for semantic analysis. Cardiovascular experts identified topics and document clusters based on the output of those semiautomatic methods. We also applied machine learning algorithms to predict the trends over the next 5 years in each field. We examined the crossover between the two cluster groups using citation relationships in the documents.</p><p><strong>Results: </strong>Research in clinical studies showed the most notable increase; that was followed by research in population and basic studies. The research hotspots were minimally invasive treatments for valve disease, circulatory haemodynamics, and prevention and control of hypertension. The fastest-growing topics were health monitoring, evidence-based medicine and immunotherapy. We found extensive crossover relationships among document clusters for the periods of 2017-2018 and 2020-2021.</p><p><strong>Conclusions: </strong>This study provides valuable insights into the research hotspots for cardiovascular research, including an increasing emphasis on early disease detection and prevention, exploration of minimally invasive treatments and assessment of risk factors. The research landscape demonstrates signs of interdisciplinarity and integration as reflected in citation relationships. These findings suggest practical implications for optimising resource allocation in healthcare systems, guiding clinical guideline updates and informing policy-making to prioritise high-impact research areas aligned with evolving CVD challenges. Given the evolving global burden of CVD, continuous research and innovation are imperative, with interdisciplinary collaboration assuming a pivotal role in advancing scientific knowledge.</p>\",\"PeriodicalId\":12835,\"journal\":{\"name\":\"Heart\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Heart\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/heartjnl-2025-325877\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Heart","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/heartjnl-2025-325877","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Analysis and prediction of cardiovascular research hotspots, trends and interdisciplinarity.
Objective: Comprehensive data and analyses on cardiovascular research could clarify recent research trends for the academic community and facilitate policy development. We examined publications and reference data to identify research topics, trends and interdisciplinarity for cardiovascular disease (CVD).
Methods: We extracted and clustered text fragments from the titles and abstracts of 2 512 445 publications using artificial intelligence techniques, including natural language processing (NLP) for semantic analysis. Cardiovascular experts identified topics and document clusters based on the output of those semiautomatic methods. We also applied machine learning algorithms to predict the trends over the next 5 years in each field. We examined the crossover between the two cluster groups using citation relationships in the documents.
Results: Research in clinical studies showed the most notable increase; that was followed by research in population and basic studies. The research hotspots were minimally invasive treatments for valve disease, circulatory haemodynamics, and prevention and control of hypertension. The fastest-growing topics were health monitoring, evidence-based medicine and immunotherapy. We found extensive crossover relationships among document clusters for the periods of 2017-2018 and 2020-2021.
Conclusions: This study provides valuable insights into the research hotspots for cardiovascular research, including an increasing emphasis on early disease detection and prevention, exploration of minimally invasive treatments and assessment of risk factors. The research landscape demonstrates signs of interdisciplinarity and integration as reflected in citation relationships. These findings suggest practical implications for optimising resource allocation in healthcare systems, guiding clinical guideline updates and informing policy-making to prioritise high-impact research areas aligned with evolving CVD challenges. Given the evolving global burden of CVD, continuous research and innovation are imperative, with interdisciplinary collaboration assuming a pivotal role in advancing scientific knowledge.
期刊介绍:
Heart is an international peer reviewed journal that keeps cardiologists up to date with important research advances in cardiovascular disease. New scientific developments are highlighted in editorials and put in context with concise review articles. There is one free Editor’s Choice article in each issue, with open access options available to authors for all articles. Education in Heart articles provide a comprehensive, continuously updated, cardiology curriculum.