Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory

Unplanned readmission of a hospitalized patient is an indicator of patients' exposure to risk and an avoidable waste of medical resources. In addition to hospital readmission, intensive care unit (ICU) readmission brings further financial risk, along with morbidity and mortality risks. Identifi...

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Veröffentlicht in:	PloS one 2019-07, Vol.14 (7), p.e0218942-e0218942
Hauptverfasser:	Lin, Yu-Wei, Zhou, Yuqian, Faghri, Faraz, Shaw, Michael J, Campbell, Roy H
Format:	Artikel
Sprache:	eng
Schlagworte:	Analysis Artificial intelligence Artificial neural networks Biology and Life Sciences Clinical decision making Computer and Information Sciences Databases, Genetic Decision making Deep learning Demographics Discharge Economic aspects Electronic health records Female Financial risk Glucose Health aspects Health care reform Health counseling Heart rate Hospital admission and discharge Hospital patients Hospitals Humans Intensive care units Intensive Care Units - statistics & numerical data Learning algorithms Long short-term memory Machine Learning Male Medical personnel Medical research Medical wastes Medicine and Health Sciences Memory, Long-Term - physiology Memory, Short-Term - physiology Middle Aged Morbidity Mortality Neural networks Neural Networks, Computer Oxygen - metabolism Patient Discharge Patient Readmission - statistics & numerical data Patients Physical Sciences Physicians Precision medicine Prediction models Recurrent neural networks Research and Analysis Methods Retirement benefits Risk assessment Risk groups Social Sciences Support systems Technology application Volatility
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