An Explainable Artificial Intelligence Approach for Discovering Social Determinants of Health and Risk Interactions for Stroke in Patients With Atrial Fibrillation.
作者信息
Zimmerman Raquel M, Hernandez Edgar J, Watkins W Scott, Blue Nathan, Tristani-Firouzi Martin, Yandell Mark, Steinberg Benjamin A
机构信息
Department of Biomedical Informatics, University of Utah, Utah.
Utah Center for Genetic Discovery, Department of Human Genetics, University of Utah, Utah.
出版信息
Am J Cardiol. 2023 Aug 15;201:224-226. doi: 10.1016/j.amjcard.2023.05.064. Epub 2023 Jun 27.
Abstract
摘要
相似文献
1
An Explainable Artificial Intelligence Approach for Discovering Social Determinants of Health and Risk Interactions for Stroke in Patients With Atrial Fibrillation.一种用于发现房颤患者健康的社会决定因素及中风风险相互作用的可解释人工智能方法。
Am J Cardiol. 2023 Aug 15;201:224-226. doi: 10.1016/j.amjcard.2023.05.064. Epub 2023 Jun 27.
2
What is next for screening for undiagnosed atrial fibrillation? Artificial intelligence may hold the key.未诊断出的心房颤动筛查的下一步是什么？人工智能可能是关键所在。
Eur Heart J Qual Care Clin Outcomes. 2022 Jun 6;8(4):391-397. doi: 10.1093/ehjqcco/qcab094.
3
Associations of Community and Individual Social Determinants of Health With Medication Adherence in Patients With Atrial Fibrillation: A Retrospective Cohort Study.社区和个体健康社会决定因素与心房颤动患者药物治疗依从性的关系：一项回顾性队列研究。
J Am Heart Assoc. 2023 Apr 18;12(8):e026745. doi: 10.1161/JAHA.122.026745. Epub 2023 Apr 7.
4
GARFIELD-AF: a worldwide prospective registry of patients with atrial fibrillation at risk of stroke.GARFIELD-AF：一项针对有卒中风险的心房颤动患者的全球性前瞻性注册研究。
Future Cardiol. 2021 Jan;17(1):19-38. doi: 10.2217/fca-2020-0014. Epub 2020 Jul 22.
5
Is low body weight a novel risk factor for thromboembolic events in patients with non-valvular atrial fibrillation?低体重是否是非瓣膜性心房颤动患者血栓栓塞事件的一个新的危险因素？
Circ J. 2015;79(5):960-1. doi: 10.1253/circj.CJ-15-0307. Epub 2015 Mar 30.
6
The Epidemiology of Atrial Fibrillation and Stroke.心房颤动与中风的流行病学
Cardiol Clin. 2016 May;34(2):255-68. doi: 10.1016/j.ccl.2015.12.002. Epub 2016 Mar 18.
7
Antithrombotic therapies for stroke prevention in atrial fibrillation.用于心房颤动中风预防的抗栓治疗。
Adv Neurol. 2003;92:249-56.
8
9
Pre-Diabetes and Stroke in Patients With Atrial Fibrillation: When Risk Begets Risk.心房颤动患者的糖尿病前期与中风：风险如何引发更多风险。
J Am Coll Cardiol. 2021 Feb 23;77(7):885-887. doi: 10.1016/j.jacc.2020.12.035.
10
Ischemic stroke in atrial fibrillation patients: don't put the blame always on heart.心房颤动患者的缺血性卒中：不要总是归咎于心脏。
Hellenic J Cardiol. 2020 May-Jun;61(3):208-209. doi: 10.1016/j.hjc.2018.07.003. Epub 2018 Sep 19.
引用本文的文献
1
Artificial intelligence in atrial fibrillation: emerging applications, research directions and ethical considerations.人工智能在心房颤动中的应用：新兴应用、研究方向及伦理考量
Front Cardiovasc Med. 2025 Jun 24;12:1596574. doi: 10.3389/fcvm.2025.1596574. eCollection 2025.
2
Probabilistic Graphical Models for Evaluating the Utility of Data-Driven ICD Code Categories in Pediatric Sepsis.用于评估数据驱动的儿科脓毒症ICD编码类别的效用的概率图模型
AMIA Annu Symp Proc. 2025 May 22;2024:1149-1158. eCollection 2024.
3
Explainable artificial intelligence for stroke risk stratification in atrial fibrillation.用于心房颤动中风风险分层的可解释人工智能
Eur Heart J Digit Health. 2025 Mar 22;6(3):317-325. doi: 10.1093/ehjdh/ztaf019. eCollection 2025 May.
4
The Efficacy of Artificial Intelligence in the Detection and Management of Atrial Fibrillation.人工智能在心房颤动检测与管理中的功效
Cureus. 2025 Jan 8;17(1):e77135. doi: 10.7759/cureus.77135. eCollection 2025 Jan.
本文引用的文献
1
Transforming Atrial Fibrillation Research to Integrate Social Determinants of Health: A National Heart, Lung, and Blood Institute Workshop Report.将心房颤动研究转化为整合健康的社会决定因素：美国国立心肺血液研究所研讨会报告。
JAMA Cardiol. 2023 Feb 1;8(2):182-191. doi: 10.1001/jamacardio.2022.4091.
2
Machine Learning-Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure.基于机器学习的纳入健康社会决定因素的模型与传统模型在预测心力衰竭患者住院死亡率中的比较。
JAMA Cardiol. 2022 Aug 1;7(8):844-854. doi: 10.1001/jamacardio.2022.1900.
3
An explainable artificial intelligence approach for predicting cardiovascular outcomes using electronic health records.一种利用电子健康记录预测心血管疾病转归的可解释人工智能方法。
PLOS Digit Health. 2022;1(1). doi: 10.1371/journal.pdig.0000004. Epub 2022 Jan 18.
4
A Poisson binomial-based statistical testing framework for comorbidity discovery across electronic health record datasets.一种基于泊松二项式的统计测试框架，用于跨电子健康记录数据集发现共病情况。
Nat Comput Sci. 2021 Oct;1(10):694-702. doi: 10.1038/s43588-021-00141-9. Epub 2021 Oct 21.
5
Association of the Estimated Glomerular Filtration Rate With vs Without a Coefficient for Race With Time to Eligibility for Kidney Transplant.种族系数与估算肾小球滤过率与获得肾脏移植资格时间的关系。
JAMA Netw Open. 2021 Jan 4;4(1):e2034004. doi: 10.1001/jamanetworkopen.2020.34004.
6
Contribution of atrial fibrillation to incidence and outcome of ischemic stroke: results from a population-based study.心房颤动对缺血性卒中发病率和预后的影响：一项基于人群研究的结果
Stroke. 2005 Jun;36(6):1115-9. doi: 10.1161/01.STR.0000166053.83476.4a. Epub 2005 May 5.
Zotero 插件