Machine learning-based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics

ESC Heart Failure
Saqib Ejaz AwanGirish Dwivedi

Abstract

Machine learning (ML) is widely believed to be able to learn complex hidden interactions from the data and has the potential in predicting events such as heart failure (HF) readmission and death. Recent studies have revealed conflicting results likely due to failure to take into account the class imbalance problem commonly seen with medical data. We developed a new ML approach to predict 30 day HF readmission or death and compared the performance of this model with other commonly used prediction models. We identified all Western Australian patients aged above 65 years admitted for HF between 2003 and 2008 in the linked Hospital Morbidity Data Collection. Taking into consideration the class imbalance problem, we developed a multi-layer perceptron (MLP)-based approach to predict 30 day HF readmission or death and compared the predictive performances using the performance metrics, that is, area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), sensitivity and specificity with other ML and regression models. Out of the 10 757 patients with HF, 23.6% were readmitted or died within 30 days of hospital discharge. We observed an AUC of 0.55, 0.53, 0.58, and 0.54 while an AUPRC of 0....Continue Reading

References

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Citations

Feb 19, 2020·Expert Review of Cardiovascular Therapy·Brijesh Patel, Partho Sengupta
Jul 15, 2020·JMIR Medical Informatics·Patrick EssayVignesh Subbian
Sep 3, 2020·Applied Clinical Informatics·Santiago Romero-BrufauCheristi Cognetta-Rieke
Dec 16, 2020·BMC Medical Informatics and Decision Making·Zhen ZhangYucheng Chen
Feb 21, 2021·European Journal of Heart Failure·Daniela Tomasoni, Andrew J S Coats
May 29, 2021·American Journal of Health-system Pharmacy : AJHP : Official Journal of the American Society of Health-System Pharmacists·Melissa R RiesterAndrew R Zullo
Aug 24, 2021·Arabian Journal for Science and Engineering·Kareen TeoKhin Wee Lai

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Software Mentioned

Keras Library
Python
scikit
Tensor Flow
LASSO
learn

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