Extracting More From Less: A New Frontier for High-Throughput Clinical Phenotyping.
作者信息
Ouyang David, Cheng Susan
机构信息
Department of Cardiology, Smidt Heart Institute (D.O., S.C.), Cedars-Sinai Medical Center, Los Angeles, CA.
Division of Artificial Intelligence in Medicine (D.O.), Cedars-Sinai Medical Center, Los Angeles, CA.
出版信息
Circ Cardiovasc Qual Outcomes. 2022 Jun;15(6):e009055. doi: 10.1161/CIRCOUTCOMES.122.009055. Epub 2022 Apr 28.
Abstract
摘要
相似文献
1
Extracting More From Less: A New Frontier for High-Throughput Clinical Phenotyping.从更少中获取更多：高通量临床表型分析的新前沿
Circ Cardiovasc Qual Outcomes. 2022 Jun;15(6):e009055. doi: 10.1161/CIRCOUTCOMES.122.009055. Epub 2022 Apr 28.
2
Applying active learning to high-throughput phenotyping algorithms for electronic health records data.将主动学习应用于电子健康记录数据的高通量表型算法。
J Am Med Inform Assoc. 2013 Dec;20(e2):e253-9. doi: 10.1136/amiajnl-2013-001945. Epub 2013 Jul 13.
3
PheMap: a multi-resource knowledge base for high-throughput phenotyping within electronic health records.PheMap：一个用于电子健康记录中高通量表型分析的多资源知识库。
J Am Med Inform Assoc. 2020 Nov 1;27(11):1675-1687. doi: 10.1093/jamia/ocaa104.
4
High-throughput phenotyping with temporal sequences.高通量表型分析与时间序列。
J Am Med Inform Assoc. 2021 Mar 18;28(4):772-781. doi: 10.1093/jamia/ocaa288.
5
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.特定国家网络中的临床表型分析：证明对高通量、便携式和计算方法的需求。
Artif Intell Med. 2016 Jul;71:57-61. doi: 10.1016/j.artmed.2016.05.005. Epub 2016 Jun 25.
6
Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.估算电子健康记录实验室数据的汇总统计信息，用于高通量表型分析算法。
J Biomed Inform. 2018 Feb;78:87-101. doi: 10.1016/j.jbi.2018.01.004. Epub 2018 Jan 31.
7
8
Phenotyping issues for exploring electronic health records to design clinical trials.探索电子健康记录以设计临床试验的表型问题。
Clin Trials. 2020 Aug;17(4):402-404. doi: 10.1177/1740774520931039. Epub 2020 Jun 10.
9
Surrogate-assisted feature extraction for high-throughput phenotyping.用于高通量表型分析的代理辅助特征提取
J Am Med Inform Assoc. 2017 Apr 1;24(e1):e143-e149. doi: 10.1093/jamia/ocw135.
10
Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.迈向高通量表型分析：从知识源中进行无偏自动特征提取与选择。
J Am Med Inform Assoc. 2015 Sep;22(5):993-1000. doi: 10.1093/jamia/ocv034. Epub 2015 Apr 29.
本文引用的文献
1
Cardiovascular Risk Assessment Using Artificial Intelligence-Enabled Event Adjudication and Hematologic Predictors.利用人工智能实现的事件裁决和血液学预测指标进行心血管风险评估。
Circ Cardiovasc Qual Outcomes. 2022 Jun;15(6):e008007. doi: 10.1161/CIRCOUTCOMES.121.008007. Epub 2022 Apr 28.
2
Deep learning evaluation of biomarkers from echocardiogram videos.基于超声心动图视频的生物标志物深度学习评估。
EBioMedicine. 2021 Nov;73:103613. doi: 10.1016/j.ebiom.2021.103613. Epub 2021 Oct 14.
3
A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study.利用心电图检测贫血的深度学习算法：一项回顾性、多中心研究。
Lancet Digit Health. 2020 Jul;2(7):e358-e367. doi: 10.1016/S2589-7500(20)30108-4. Epub 2020 Jun 23.
4
Deep learning models to detect hidden clinical correlates.用于检测隐藏临床关联的深度学习模型。
Lancet Digit Health. 2020 Jul;2(7):e334-e335. doi: 10.1016/S2589-7500(20)30138-2. Epub 2020 Jun 23.
5
Ferric carboxymaltose for iron deficiency at discharge after acute heart failure: a multicentre, double-blind, randomised, controlled trial.铁羧基麦芽糖治疗急性心力衰竭出院后缺铁：一项多中心、双盲、随机、对照试验。
Lancet. 2020 Dec 12;396(10266):1895-1904. doi: 10.1016/S0140-6736(20)32339-4. Epub 2020 Nov 13.
6
Restrictive or Liberal Red-Cell Transfusion for Cardiac Surgery.心脏手术中红细胞的限制输血或自由输血。
N Engl J Med. 2017 Nov 30;377(22):2133-2144. doi: 10.1056/NEJMoa1711818. Epub 2017 Nov 12.
7
Machine Learning and Prediction in Medicine - Beyond the Peak of Inflated Expectations.医学中的机器学习与预测——超越过高期望的顶峰
N Engl J Med. 2017 Jun 29;376(26):2507-2509. doi: 10.1056/NEJMp1702071.
8
Lower versus higher hemoglobin threshold for transfusion in septic shock.较低与较高血红蛋白阈值用于感染性休克患者输血。
N Engl J Med. 2014 Oct 9;371(15):1381-91. doi: 10.1056/NEJMoa1406617. Epub 2014 Oct 1.
9
Age-related left ventricular remodeling and associated risk for cardiovascular outcomes: the Multi-Ethnic Study of Atherosclerosis.年龄相关的左心室重构及心血管结局的相关风险：动脉粥样硬化多族裔研究
Circ Cardiovasc Imaging. 2009 May;2(3):191-8. doi: 10.1161/CIRCIMAGING.108.819938. Epub 2009 Mar 26.
Zotero 插件