[HTML][HTML] Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory
Background 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 …
exposure to risk and an avoidable waste of medical resources. In addition to hospital …
[HTML][HTML] Benchmarking deep learning architectures for predicting readmission to the ICU and describing patients-at-risk
S Barbieri, J Kemp, O Perez-Concha, S Kotwal… - Scientific reports, 2020 - nature.com
To compare different deep learning architectures for predicting the risk of readmission within
30 days of discharge from the intensive care unit (ICU). The interpretability of attention …
30 days of discharge from the intensive care unit (ICU). The interpretability of attention …
Predicting ICU readmission using grouped physiological and medication trends
Background Patients who are readmitted to an intensive care unit (ICU) usually have a high
risk of mortality and an increased length of stay. ICU readmission risk prediction may help …
risk of mortality and an increased length of stay. ICU readmission risk prediction may help …
Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach
Objectives Unplanned readmissions to the intensive care unit (ICU) are highly undesirable,
increasing variance in care, making resource planning difficult and potentially increasing …
increasing variance in care, making resource planning difficult and potentially increasing …
Predicting intensive care unit readmission with machine learning using electronic health record data
JC Rojas, KA Carey, DP Edelson… - Annals of the …, 2018 - atsjournals.org
Rationale: Patients transferred from the intensive care unit to the wards who are later
readmitted to the intensive care unit have increased length of stay, healthcare expenditure …
readmitted to the intensive care unit have increased length of stay, healthcare expenditure …
Monitoring ICU mortality risk with a long short-term memory recurrent neural network
In intensive care units (ICU), mortality prediction is a critical factor not only for effective
medical intervention but also for allocation of clinical resources. Structured electronic health …
medical intervention but also for allocation of clinical resources. Structured electronic health …
[HTML][HTML] An attention based deep learning model of clinical events in the intensive care unit
This study trained long short-term memory (LSTM) recurrent neural networks (RNNs)
incorporating an attention mechanism to predict daily sepsis, myocardial infarction (MI), and …
incorporating an attention mechanism to predict daily sepsis, myocardial infarction (MI), and …
[HTML][HTML] Predicting unplanned transfers to the intensive care unit: a machine learning approach leveraging diverse clinical elements
B Wellner, J Grand, E Canzone, M Coarr… - JMIR medical …, 2017 - medinform.jmir.org
Background: Early warning scores aid in the detection of pediatric clinical deteriorations but
include limited data inputs, rarely include data trends over time, and have limited validation …
include limited data inputs, rarely include data trends over time, and have limited validation …
Predicting hospital readmission via cost-sensitive deep learning
With increased use of electronic medical records (EMRs), data mining on medical data has
great potential to improve the quality of hospital treatment and increase the survival rate of …
great potential to improve the quality of hospital treatment and increase the survival rate of …
[HTML][HTML] Readmission prediction using deep learning on electronic health records
Unscheduled 30-day readmissions are a hallmark of Congestive Heart Failure (CHF)
patients that pose significant health risks and escalate care cost. In order to reduce …
patients that pose significant health risks and escalate care cost. In order to reduce …