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Predicting all-cause risk of 30-day hospital readmission using artificial neural networks
2017
PLoS ONE
Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for patients. Large scale adoption of Electronic Health Records (EHR) has created the opportunity to proactively identify patients with high risk of hospital readmission, and apply effective interventions to mitigate that risk. To that end, in the past, numerous machine-learning models have been employed to predict the risk of 30-day hospital readmission.
doi:10.1371/journal.pone.0181173
pmid:28708848
pmcid:PMC5510858
fatcat:h5kiczd5vzbkbplmhkzyf6nezi