[The quality assurance and device register of the German Institute for Vascular Medicine Health Research (DGG) in the COVID-19 era, big data and artificial intelligence].
作者信息
Behrendt Christian-Alexander, Adili Farzin, Böckler Dittmar, Cotta Livia, Görtz Hartmut, Heckenkamp Jörg, Peter Jochen, Schmandra Thomas, Stojanovic Tomislav, Uhl Christian, Steinbauer Markus
机构信息
Deutsches Institut für Gefäßmedizinische Gesundheitsforschung (DIGG gGmbH), Deutsche Gesellschaft für Gefäßchirurgie und Gefäßmedizin, Gesellschaft für operative, endovaskuläre und präventive Gefäßmedizin (DGG e. V.), Robert-Koch-Platz 9, 10115 Berlin, Deutschland.
Medical Device Epidemiology Network (MDEpiNet) Verband Deutschland e. V., Hamburg, Deutschland.
出版信息
Gefasschirurgie. 2022;27(5):317-320. doi: 10.1007/s00772-022-00916-y. Epub 2022 Sep 7.
Abstract
摘要
相似文献
1
[The quality assurance and device register of the German Institute for Vascular Medicine Health Research (DGG) in the COVID-19 era, big data and artificial intelligence].[德国血管医学健康研究所在新冠疫情时代的质量保证与设备登记、大数据及人工智能]
Gefasschirurgie. 2022;27(5):317-320. doi: 10.1007/s00772-022-00916-y. Epub 2022 Sep 7.
2
Use of Big Data for Quality Assurance in Radiation Therapy.大数据在放射治疗质量保证中的应用。
Semin Radiat Oncol. 2019 Oct;29(4):326-332. doi: 10.1016/j.semradonc.2019.05.006.
3
New Opportunities and Challenges for Forensic Medicine in the Era of Artificial Intelligence Technology.人工智能技术时代法医学的新机遇与挑战
Fa Yi Xue Za Zhi. 2020 Feb;36(1):77-85. doi: 10.12116/j.issn.1004-5619.2020.01.016.
4
For a critical appraisal of artificial intelligence in healthcare: The problem of bias in mHealth.人工智能在医疗保健领域的批判性评价：移动医疗中的偏见问题。
J Eval Clin Pract. 2021 Jun;27(3):513-519. doi: 10.1111/jep.13528. Epub 2020 Dec 23.
5
[the German Pacemaker Register].[德国起搏器登记处]
Herzschrittmacherther Elektrophysiol. 2010 Dec;21(4):248-55. doi: 10.1007/s00399-010-0110-1.
6
Big data requirements for artificial intelligence.人工智能的大数据需求。
Curr Opin Ophthalmol. 2020 Sep;31(5):318-323. doi: 10.1097/ICU.0000000000000676.
7
[Artificial intelligence provides promotion of big data in medical work and contribution to people's health as soon as possible: real-time warning of critical illness is the pioneer of artificial intelligence in clinical medicine].[人工智能推动医学工作中的大数据发展，尽快为人们的健康做出贡献：危重症实时预警是人工智能在临床医学中的先锋应用]
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2020 Oct;32(10):1155-1159. doi: 10.3760/cma.j.cn121430-20200719-00567.
8
Improving the Quality of Care in Radiation Oncology using Artificial Intelligence.利用人工智能提高放射肿瘤学的护理质量。
Clin Oncol (R Coll Radiol). 2022 Feb;34(2):89-98. doi: 10.1016/j.clon.2021.11.011. Epub 2021 Dec 7.
9
Big Data and Artificial Intelligence Modeling for Drug Discovery.大数据和人工智能在药物发现中的建模。
Annu Rev Pharmacol Toxicol. 2020 Jan 6;60:573-589. doi: 10.1146/annurev-pharmtox-010919-023324. Epub 2019 Sep 13.
10
Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases.让世界恢复运转：一种利用大数据和人工智能抗击新冠疫情及类似传染病传播的专家系统。
Work. 2020;67(3):557-572. doi: 10.3233/WOR-203309.
引用本文的文献
1
[Recommendations for the specialist further training of nursing personnel on intensive care units in the treatment of abdominal aortic aneurysms: results of a modified Delphi procedure with experts].[关于重症监护病房护理人员在腹主动脉瘤治疗方面专科进阶培训的建议：专家改良德尔菲法的结果]
Chirurgie (Heidelb). 2024 May;95(5):395-405. doi: 10.1007/s00104-024-02066-1. Epub 2024 Mar 18.
本文引用的文献
1
Big Data and Artificial Intelligence in Vascular Surgery: Time for Multidisciplinary Cross-Border Collaboration.血管外科中的大数据与人工智能：多学科跨境合作的时机已到。
Angiology. 2022 Sep;73(8):697-700. doi: 10.1177/00033197221113146. Epub 2022 Jul 10.
2
Use of data from the Vascular Quality Initiative registry to support regulatory decisions yielded a high return on investment.利用血管质量倡议登记处的数据来支持监管决策产生了高投资回报率。
BMJ Surg Interv Health Technol. 2020 Oct 30;2(1):e000039. doi: 10.1136/bmjsit-2020-000039. eCollection 2020.
3
The prospective GermanVasc cohort study.德国血管前瞻性队列研究。
Vasa. 2021 Nov;50(6):446-452. doi: 10.1024/0301-1526/a000966. Epub 2021 Jul 19.
4
[The first impact and collateral damage of the corona pandemic in interdisciplinary vascular medicine: vaccination campaign for patients with peripheral arterial disease?].[新冠疫情在跨学科血管医学中的首次冲击及附带损害：外周动脉疾病患者的疫苗接种活动？]
Gefasschirurgie. 2021;26(3):151-153. doi: 10.1007/s00772-021-00769-x. Epub 2021 Apr 28.
5
Big data in vascular surgery: registries, international collaboration and future directions.血管外科学中的大数据：注册研究、国际合作和未来方向。
J Intern Med. 2020 Jul;288(1):51-61. doi: 10.1111/joim.13077. Epub 2020 May 14.
6
Disruptive and avoidable: GDPR challenges to secondary research uses of data.破坏性行为与可避免性：GDPR 对数据二次研究使用的挑战。
Eur J Hum Genet. 2020 Jun;28(6):697-705. doi: 10.1038/s41431-020-0596-x. Epub 2020 Mar 2.
7
VASCUNET, VQI, and the International Consortium of Vascular Registries - Unique Collaborations for Quality Improvement in Vascular Surgery.血管网络（VASCUNET）、血管质量倡议（VQI）以及国际血管注册机构联盟——血管外科质量改进的独特合作。
Eur J Vasc Endovasc Surg. 2019 Dec;58(6):792-793. doi: 10.1016/j.ejvs.2019.07.023. Epub 2019 Aug 14.
8
Editor's Choice - Recommendations for Registry Data Collection for Revascularisations of Acute Limb Ischaemia: A Delphi Consensus from the International Consortium of Vascular Registries.编辑精选 - 急性肢体缺血血运重建注册数据采集建议：国际血管登记研究联合会的德尔菲共识。
Eur J Vasc Endovasc Surg. 2019 Jun;57(6):816-821. doi: 10.1016/j.ejvs.2019.02.023. Epub 2019 May 22.
9
Data Privacy Compliant Validation of Health Insurance Claims Data: the IDOMENEO Approach.符合数据隐私要求的健康保险理赔数据验证：伊多梅内奥方法
Gesundheitswesen. 2020 Mar;82(S 02):S94-S100. doi: 10.1055/a-0883-5098. Epub 2019 May 23.
10
[The DIGG risk score : A risk predictive model of perioperative mortality after elective treatment of intact abdominal aortic aneurysms in the DIGG register].[DIGG风险评分：DIGG登记册中择期治疗完整腹主动脉瘤后围手术期死亡率的风险预测模型]
Chirurg. 2019 Nov;90(11):913-920. doi: 10.1007/s00104-019-0968-3.
Zotero 插件