[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121295-en":3,"doc-seo-121295-105":30,"detail-sidebar-cat-0-en-105":95},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121295,1099514067415,"Rowan","https://ap-avatar.wpscdn.com/avatar/100002539d78ffe74a7?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779092875211072502",8,"Research & Report","Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis - a bibliometric analysis (2004–2023)","Objective: examine research focal areas in early stroke diagnosis through machine learning identification of magnetic resonance imaging characteristics from 2004 to 2023. Methods: bibliometric data were retrieved from the Science Citation Index-Expanded within Web of Science Core Collection and analyzed with CiteSpace 6.2.R6 across publications, authors, countries, institutions, journals, references, and keywords. Results: 395 articles were included; publication growth accelerated after 2015, with strong US-China collaboration and prominent high-impact journals. Conclusions: ML using neuroimaging features supports early prediction and personalized care; hotspots include optimal neural imaging markers and suitable algorithm models.","TYPE Systematic Review PUBLISHED 14 March 2025  \nDOI 10.3389/fneur.2025.1505533  \nOPEN ACCESS  \nEDITED BY  \nMingming Lu,  \nCharacteristic Medical Center of Chinese People’s Armed Police Force, China  \nREVIEWED BY  \nHan Cong,  \nFifth Medical Center of the PLA General Hospital, China  \nFrancesca Galassi,  \nUniversity of Rennes 1, France Baobao Li,  \nFifth Medical Center of the PLA General Hospital, China  \n*CORRESPONDENCE  \nWen-hua Xiong  \n [xiongwenhua3@163.com](xiongwenhua3@163.com)  \nRECEIVED 03 October 2024  \nACCEPTED 24 February 2025  \nPUBLISHED 14 March 2025  \nCITATION  \nLou J-c, Yu X-f, Ying J-j, Song D-q and Xiong W-h (2025) Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: abibliometric analysis (2004–2023) .  \nFront. Neurol. 16:1505533 .  \ndoi: 10.3389/fneur.2025.1505533  \nCOPYRIGHT  \n© 2025 Lou, Yu, Ying, Song and Xiong. This isan open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nExploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: a bibliometric analysis (2004–2023)  \nJian-cheng Lou, Xiao-fen Yu, Jian-jun Ying, Da-qiao Song and Wen-hua Xiong *  \nYiwu Hospital of Traditional Chinese Medicine, Yiwu, China  \nObjective: To examine the focal areas of research in the early diagnosis of stroke through machine learning identification of magnetic resonance imaging characteristics from 2004 to 2023.  \nMethods: Data were gathered from the Science Citation Index-Expanded (SCI-E) within the Web of Science Core Collection (WoSCC) . Utilizing CiteSpace 6.2. R6, a thorough analysis was conducted, encompassing publications, authors, cited authors, countries, institutions, cited journals, references, and keywords. This investigation covered the period from 2004 to 2023, with the data retrieval completed on December 1, 2023, in a single day.  \nResults: In total, 395 articles were incorporated into the analysis. Prior to 2015, the annual publication count was under 10, but a significant surge in publications was observed post-2015 . Institutions and authors from the USA and China have established themselves as mature academic entities on a global scale, forging extensive collaborative networks with other institutions. High-impact journals in this field predominantly feature in top-tier publications, indicating a consensus in the medical community on the application of machine learning for early stroke diagnosis.“deep learning,”“magnetic resonance imaging,” and “stroke”emerged as the most attention-gathering keywords among researchers. The development in this field is marked by a coexisting pattern of interdisciplinary integration and refinement within major disciplinary branches.  \nConclusion: The application of machine learning in the early prediction and personalized medical plans for stroke patients using neuroimaging characteristics offers significant value. The most notable research hotspots currently are the optimal selection of neural imaging markers and the most suitable machine learning algorithm models.  \nKEYWORDS  \nstroke, machine learning, magnetic resonance imaging, bibliometric analysis, WoSCC  \nIntroduction  \nStroke is an acute cerebrovascular disorder, precipitates enduring cerebral damage, disability, and even mortality upon its onset ( 1–3) . Studies have identified it as the second leading cause of death worldwide (4). Notably, 11% of stroke survivors experience a recurrence within a year, and 39% within a decade (5) . Generally, strokes arise either from blood flow  \nFrontiers in Neurology 01 [frontiersin.org](frontiersin.org)  \nobstr","cbCaiirQNsrTssHw","https://ap.wps.com/l/cbCaiirQNsrTssHw","pdf",3938105,1,14,"English","en",105,"# Introduction\n## Stroke epidemiology and need for early diagnosis\n## Role of magnetic resonance imaging (MRI)\n## Machine learning for automated risk assessment\n# Objective\n# Methods\n## Data sources and retrieval period\n## Bibliometric tools and scope\n# Results\n## Publication trends\n## Collaboration patterns and leading journals\n## Keyword emergence\n# Conclusion","[{\"question\":\"What was the study objective regarding early stroke diagnosis?\",\"answer\":\"To identify research focal areas in early stroke diagnosis by examining machine-learning-driven interpretations of MRI characteristics from 2004 to 2023.\"},{\"question\":\"How were the publications and scholarly factors analyzed?\",\"answer\":\"Data were collected from SCI-E in the Web of Science Core Collection and analyzed using CiteSpace 6.2.R6, covering publications, authors, countries, institutions, journals, references, and keywords.\"},{\"question\":\"What were the key findings about publication trends and collaboration?\",\"answer\":\"Total 395 articles were included, with publication counts accelerating notably after 2015. The USA and China showed mature academic presence and extensive collaboration networks.\"},{\"question\":\"Which research hotspots were highlighted for future work?\",\"answer\":\"Selecting optimal neural imaging markers and determining the most suitable machine learning algorithm models for early prediction and personalized stroke care.\"}]","Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis - a bibliometric analysis (2004–2023) | PDF",1785734949,35,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":90,"head_meta":92,"extra_data":94,"updated_unix":28},"exploring-the-potential-of-machine-learning-and-magnetic-resonance-imaging-in-early-stroke-diagnosis-a-bibliometric-analysis-20042023","",{"@graph":36,"@context":89},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/exploring-the-potential-of-machine-learning-and-magnetic-resonance-imaging-in-early-stroke-diagnosis-a-bibliometric-analysis-20042023/121295/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81,85],{"name":72,"@type":73,"acceptedAnswer":74},"What was the study objective regarding early stroke diagnosis?","Question",{"text":75,"@type":76},"To identify research focal areas in early stroke diagnosis by examining machine-learning-driven interpretations of MRI characteristics from 2004 to 2023.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were the publications and scholarly factors analyzed?",{"text":80,"@type":76},"Data were collected from SCI-E in the Web of Science Core Collection and analyzed using CiteSpace 6.2.R6, covering publications, authors, countries, institutions, journals, references, and keywords.",{"name":82,"@type":73,"acceptedAnswer":83},"What were the key findings about publication trends and collaboration?",{"text":84,"@type":76},"Total 395 articles were included, with publication counts accelerating notably after 2015. The USA and China showed mature academic presence and extensive collaboration networks.",{"name":86,"@type":73,"acceptedAnswer":87},"Which research hotspots were highlighted for future work?",{"text":88,"@type":76},"Selecting optimal neural imaging markers and determining the most suitable machine learning algorithm models for early prediction and personalized stroke care.","https://schema.org",{"og:url":52,"og:type":91,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":93,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":96},[97,101,105,109,114,119,124,127,132,135,139],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Exam",70,"exam",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},5,"Comic",60,"comic",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},6,"Technology",50,"technology",{"id":120,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":122,"slug":123},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":125,"slug":126},30,"research-report",{"id":128,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":130,"slug":131},9,"Religion & Spirituality",20,"religion-spirituality",{"id":130,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":130,"slug":134},"World Cup","world-cup",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":136,"slug":138},10,"Lifestyle","lifestyle",{"id":140,"doc_module":4,"doc_module_name":46,"category_name":141,"show_sort_weight":110,"slug":142},19,"General","general"]