PERFORMANCE OF MACHINE LEARNING ALGORITHMS IN PREDICTING 30 DAY HEART FAILURE READMISSIONS RISK USING AN ADMINISTRATIVE CLAIMS DATABASE

Dave C.; Park H.; Hartzema A.

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PERFORMANCE OF MACHINE LEARNING ALGORITHMS IN PREDICTING 30 DAY HEART FAILURE READMISSIONS RISK USING AN ADMINISTRATIVE CLAIMS DATABASE

机译：使用管理索赔数据库预测30天心力衰竭Readmissions风险的机器学习算法的性能

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《Value in health: the journal of the International Society for Pharmacoeconomics and Outcomes Research》 |2017年第5期|共1页
作者
Dave C.; Park H.; Hartzema A.;
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作者单位

Univ Florida Gainesville FL USA;

Univ Florida Gainesville FL USA;

Univ Florida Gainesville FL USA;

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原文格式 PDF
正文语种 eng
中图分类预防医学、卫生学;
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1. PERFORMANCE OF MACHINE LEARNING ALGORITHMS IN PREDICTING 30 DAY HEART FAILURE READMISSIONS RISK USING AN ADMINISTRATIVE CLAIMS DATABASE [J] . Dave C., Park H., Hartzema A. Value in health: the journal of the International Society for Pharmacoeconomics and Outcomes Research . 2017,第5期

机译：使用管理索赔数据库预测30天心力衰竭Readmissions风险的机器学习算法的性能
2. Predictors of 30-Day Readmission in Patients with Heart Failure - A Comparison of Risk Profile and Readmission Rates in Patients Having Heart Failure with Preserved Ejection Fraction Versus Heart Failure with Reduced Ejection Fraction [J] . Journal of cardiac failure . 2013,第8Suppla1期

机译：心力衰竭患者30天再入院的预测指标-保留射血分数的心力衰竭患者与降低射血分数的心力衰竭的风险特征和再入院率的比较
3. Unplanned Readmissions after Hospital Discharge among Heart Failure Patients At Risk for 30-Day Readmission Using an Administrative Dataset and “Off the Shelf” Readmission Models [J] . James F. Reed, Jonna L. Bokovoy, Keith R. Doram The Internet Journal of Cardiovascular Research . 2014,第1期

机译：使用管理数据集和“现成”的再入院模型，有心衰患者的30天再入院风险中的出院后计划外入院
4. Predicting 30-day Readmission in Heart Failure using Machine Learning Techniques [C] . Jon Kerexeta, Arkaitz Artetxe, Vanessa Escolar, International Joint Conference on Biomedical Engineering Systems and Technologies . 2018

机译：使用机器学习技术预测心力衰竭30天的阅览室
5. Predictors of 30-Day Heart Failure Readmissions [D] . Bangiyev, Ronald. 2019

机译：30天心力衰竭预备的预测因素
6. A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data [O] . Sara Bersche Golas, Takuma Shibahara, Stephen Agboola, 2018

机译：预测心力衰竭患者30天再次入院风险的机器学习模型：电子病历数据的回顾性分析
7. Prospective Real-World Performance Evaluation of a Machine Learning Algorithm to Predict 30-Day Readmissions in Patients with Heart Failure Using Electronic Medical Record Data [O] . Sujay S Kakarmath, Neda Derakhshani, Sara B Golas, 2018

机译：使用电子医疗记录数据预测心力衰竭患者30天入伍的机器学习算法的预期真实绩效评估

PERFORMANCE OF MACHINE LEARNING ALGORITHMS IN PREDICTING 30 DAY HEART FAILURE READMISSIONS RISK USING AN ADMINISTRATIVE CLAIMS DATABASE

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