• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

Commentary: "Multimodality advanced cardiovascular and molecular imaging for early detection and monitoring of cancer therapy-associated cardiotoxicity and the role of artificial intelligence and big data".

作者信息

Sun Louise Y, Echefu Gift, Doshi Krishna, Roberts Michelle L, Hamid Abdulaziz, Cheng Richard K, Olson Jessica, Brown Sherry-Ann

机构信息

Division of Cardiothoracic Anesthesiology, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, United States.

Department of Internal Medicine, Baton Rouge General Medical Center, Baton Rouge, LA, United States.

出版信息

Front Cardiovasc Med. 2023 Feb 27;10:982028. doi: 10.3389/fcvm.2023.982028. eCollection 2023.

DOI:10.3389/fcvm.2023.982028
PMID:36923958
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10009261/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a09/10009261/93d672dfef91/fcvm-10-982028-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a09/10009261/93d672dfef91/fcvm-10-982028-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a09/10009261/93d672dfef91/fcvm-10-982028-g0001.jpg

相似文献

1
Commentary: "Multimodality advanced cardiovascular and molecular imaging for early detection and monitoring of cancer therapy-associated cardiotoxicity and the role of artificial intelligence and big data".评论：“用于癌症治疗相关心脏毒性早期检测与监测的多模态先进心血管和分子成像以及人工智能和大数据的作用”
Front Cardiovasc Med. 2023 Feb 27;10:982028. doi: 10.3389/fcvm.2023.982028. eCollection 2023.
2
Multimodality Advanced Cardiovascular and Molecular Imaging for Early Detection and Monitoring of Cancer Therapy-Associated Cardiotoxicity and the Role of Artificial Intelligence and Big Data.用于癌症治疗相关心脏毒性早期检测和监测的多模态先进心血管与分子成像以及人工智能和大数据的作用
Front Cardiovasc Med. 2022 Mar 15;9:829553. doi: 10.3389/fcvm.2022.829553. eCollection 2022.
3
Advances in Multimodality Imaging in Cardio-Oncology: JACC State-of-the-Art Review.多模态成像在心血管肿瘤学中的进展：JACC 最新综述。
J Am Coll Cardiol. 2022 Oct 18;80(16):1560-1578. doi: 10.1016/j.jacc.2022.08.743.
4
Cardio-oncology: the role of advanced echocardiography in cancer patients.心脏肿瘤学：先进超声心动图在癌症患者中的作用
Expert Rev Cardiovasc Ther. 2018 Apr;16(4):249-258. doi: 10.1080/14779072.2018.1443394. Epub 2018 Feb 22.
5
The EACVI survey on cardiac imaging in cardio-oncology.欧洲心血管影像学会心血管肿瘤学心脏影像学调查
Eur Heart J Cardiovasc Imaging. 2021 Mar 22;22(4):367-371. doi: 10.1093/ehjci/jeaa111.
6
Advanced Echocardiographic Techniques in Cardio-Oncology: the Role for Early Detection of Cardiotoxicity.心血管肿瘤学中的高级超声心动图技术：早期检测心脏毒性的作用。
Curr Cardiol Rep. 2022 Sep;24(9):1109-1116. doi: 10.1007/s11886-022-01728-y. Epub 2022 Jul 26.
7
Artificial intelligence modelling to assess the risk of cardiovascular disease in oncology patients.用于评估肿瘤患者心血管疾病风险的人工智能建模
Eur Heart J Digit Health. 2023 May 8;4(4):302-315. doi: 10.1093/ehjdh/ztad031. eCollection 2023 Aug.
8
The use of cardiovascular magnetic resonance as an early non-invasive biomarker for cardiotoxicity in cardio-oncology.心血管磁共振成像作为心脏肿瘤学中心脏毒性早期非侵入性生物标志物的应用。
Cardiovasc Diagn Ther. 2020 Jun;10(3):610-624. doi: 10.21037/cdt-20-165.
9
Pursuing Connectivity in Cardio-Oncology Care-The Future of Telemedicine and Artificial Intelligence in Providing Equity and Access to Rural Communities.追求心血管肿瘤护理中的连通性——远程医疗和人工智能在为农村社区提供公平医疗服务和就医机会方面的未来。
Front Cardiovasc Med. 2022 Jun 13;9:927769. doi: 10.3389/fcvm.2022.927769. eCollection 2022.
10
Role of advanced cardiovascular imaging in chemotherapy-induced cardiotoxicity.先进心血管成像在化疗所致心脏毒性中的作用
Heliyon. 2023 Apr 5;9(4):e15226. doi: 10.1016/j.heliyon.2023.e15226. eCollection 2023 Apr.

引用本文的文献

1
The Digital Revolution in Medicine: Applications in Cardio-Oncology.医学中的数字革命：在心脏肿瘤学中的应用
Curr Treat Options Cardiovasc Med. 2025 Dec;27(1). doi: 10.1007/s11936-024-01059-x. Epub 2024 Nov 5.

本文引用的文献

1
Multimodality Advanced Cardiovascular and Molecular Imaging for Early Detection and Monitoring of Cancer Therapy-Associated Cardiotoxicity and the Role of Artificial Intelligence and Big Data.用于癌症治疗相关心脏毒性早期检测和监测的多模态先进心血管与分子成像以及人工智能和大数据的作用
Front Cardiovasc Med. 2022 Mar 15;9:829553. doi: 10.3389/fcvm.2022.829553. eCollection 2022.
2
Cardiotoxicity risk factors with immune checkpoint inhibitors.免疫检查点抑制剂的心脏毒性风险因素。
Cardiooncology. 2022 Mar 11;8(1):3. doi: 10.1186/s40959-022-00130-5.
3
Inequity in Cardio-Oncology: Identifying Disparities in Cardiotoxicity and Links to Cardiac and Cancer Outcomes.
心血管肿瘤学中的不公平现象：识别心脏毒性的差异及其与心脏和癌症结局的关联。
J Am Heart Assoc. 2021 Dec 21;10(24):e023852. doi: 10.1161/JAHA.121.023852. Epub 2021 Dec 16.
4
Florida Inter-Specialty Collaborative Project to Improve Cardio-Oncology Awareness and Identify Existing Knowledge Gaps.佛罗里达跨专业合作项目，旨在提高心脏肿瘤学认知并识别现有知识差距。
JACC CardioOncol. 2020 Sep 15;2(3):535-538. doi: 10.1016/j.jaccao.2020.06.009. eCollection 2020 Sep.
5
Multiparametric Early Detection and Prediction of Cardiotoxicity Using Myocardial Strain, T1 and T2 Mapping, and Biochemical Markers: A Longitudinal Cardiac Resonance Imaging Study During 2 Years of Follow-Up.使用心肌应变、T1 和 T2 映射及生化标志物进行多参数早期心脏毒性检测和预测：2 年随访期间的纵向心脏磁共振成像研究。
Circ Cardiovasc Imaging. 2021 Jun;14(6):e012459. doi: 10.1161/CIRCIMAGING.121.012459. Epub 2021 Jun 15.
6
Modeling Precision Cardio-Oncology: Using Human-Induced Pluripotent Stem Cells for Risk Stratification and Prevention.精准心脏肿瘤学建模：利用人诱导多能干细胞进行风险分层和预防。
Curr Oncol Rep. 2021 May 3;23(7):77. doi: 10.1007/s11912-021-01066-2.
7
Early Detection of Checkpoint Inhibitor-Associated Myocarditis Using Ga-FAPI PET/CT.使用镓标记的纤维连接蛋白激活肽正电子发射断层扫描/计算机断层扫描（Ga-FAPI PET/CT）早期检测检查点抑制剂相关心肌炎
Front Cardiovasc Med. 2021 Feb 25;8:614997. doi: 10.3389/fcvm.2021.614997. eCollection 2021.
8
Perspectives on the COVID-19 pandemic impact on cardio-oncology: results from the COVID-19 International Collaborative Network survey.关于新冠疫情对心脏肿瘤学影响的观点：来自新冠国际协作网络调查的结果
Cardiooncology. 2020 Nov 27;6(1):28. doi: 10.1186/s40959-020-00085-5.
9
How to Implement AI in the Clinical Enterprise: Opportunities and Lessons Learned.如何在临床机构中实施人工智能：机遇与经验教训。
J Am Coll Radiol. 2020 Nov;17(11):1394-1397. doi: 10.1016/j.jacr.2020.09.039.
10
Predicting population health with machine learning: a scoping review.利用机器学习预测人群健康：一项范围综述
BMJ Open. 2020 Oct 27;10(10):e037860. doi: 10.1136/bmjopen-2020-037860.