Application of non-invasive imaging in myocardial infarction: a bibliometric analysis from January 2003 to December 2022
Our bibliometric analysis revealed that MI non-invasive imaging is a rapidly developing field, with emerging trends in multimodal imaging and artificial intelligence (AI). These findings suggest that the integration of various imaging techniques and the use of AI could enhance the clinical application of MI non-invasive imaging, particularly in terms of early diagnosis, risk stratification, and personalized treatment strategies.
Authors
- Haibo Ren (ORCID: https://orcid.org/0000-0001-7183-2670)
- Yinping Leng
- Yaya Zhao (ORCID: https://orcid.org/0000-0001-6424-8687)
- Lianggeng Gong (ORCID: https://orcid.org/0000-0002-5012-9393)
- WU Xin-wen
- Pei Yang (ORCID: https://orcid.org/0000-0003-0102-6272)
- Jiahui Zhang (ORCID: https://orcid.org/0000-0002-2013-0289)
- Mengyao Hu (ORCID: https://orcid.org/0000-0002-8833-7702)
- Xuan Xiao (ORCID: https://orcid.org/0009-0008-5064-8012)
- Q Y Ye
Institutions
- Nanchang University (CN)
- Jiangxi Provincial Academy of Medical Sciences (CN)
- Second Affiliated Hospital of Nanchang University (CN)
- National Heart Centre Singapore (SG)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-07-01
- DOI
- https://doi.org/10.21037/qims-24-878
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00