The secondary use of electronic health records for data mining: Data characteristics and challenges
The primary objective of implementing Electronic Health Records (EHRs) is to improve the
management of patients' health-related information. However, these records have also been …
management of patients' health-related information. However, these records have also been …
Utility of models to predict 28-day or 30-day unplanned hospital readmissions: an updated systematic review
Objective To update previous systematic review of predictive models for 28-day or 30-day
unplanned hospital readmissions. Design Systematic review. Setting/data source CINAHL …
unplanned hospital readmissions. Design Systematic review. Setting/data source CINAHL …
Use of electronic medical records in development and validation of risk prediction models of hospital readmission: systematic review
Objective To provide focused evaluation of predictive modeling of electronic medical record
(EMR) data to predict 30 day hospital readmission. Design Systematic review. Data source …
(EMR) data to predict 30 day hospital readmission. Design Systematic review. Data source …
Predictive models for hospital readmission risk: A systematic review of methods
Objectives Hospital readmission risk prediction facilitates the identification of patients
potentially at high risk so that resources can be used more efficiently in terms of cost-benefit …
potentially at high risk so that resources can be used more efficiently in terms of cost-benefit …
Development and validation of a deep neural network model for prediction of postoperative in-hospital mortality
Abstract Editor's Perspective What We Already Know about This Topic Robust predictions
are required to compare perioperative mortality among hospitals Deep neural network …
are required to compare perioperative mortality among hospitals Deep neural network …
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 …
A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models
Objective Health care providers increasingly rely upon predictive algorithms when making
important treatment decisions, however, evidence indicates that these tools can lead to …
important treatment decisions, however, evidence indicates that these tools can lead to …
Metapred: Meta-learning for clinical risk prediction with limited patient electronic health records
In recent years, large amounts of health data, such as patient Electronic Health Records
(EHR), are becoming readily available. This provides an unprecedented opportunity for …
(EHR), are becoming readily available. This provides an unprecedented opportunity for …
Predicting allcause readmissions using electronic health record data from the entire hospitalization: model development and comparison
OK Nguyen, AN Makam, C Clark… - Journal of hospital …, 2016 - Wiley Online Library
BACKGROUND Incorporating clinical information from the full hospital course may improve
prediction of 30day readmissions. OBJECTIVE To develop an allcause readmissions risk …
prediction of 30day readmissions. OBJECTIVE To develop an allcause readmissions risk …
Big data and targeted machine learning in action to assist medical decision in the ICU
Historically, personalised medicine has been synonymous with pharmacogenomics and
oncology. We argue for a new framework for personalised medicine analytics that …
oncology. We argue for a new framework for personalised medicine analytics that …