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Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

All cosine PSM results are from Lee et al [14].Number of similar patients at best predictive performanceBest predictive performance, mean (95% CI)AUROCaAUPRCbAUROCAUPRCRFc PSMdCosine PSMRF PSMCosine PSMRF PSMCosine PSMNo PSMRF PSMCosine PSMNo PSMDCe260100230600.801

Joon Lee

JMIR Med Inform 2017;5(1):e3


Patient Similarity in Prediction Models Based on Health Data: A Scoping Review

Patient Similarity in Prediction Models Based on Health Data: A Scoping Review

Although Lee et al [39] suggested that computational load can be parallelized, the high computational load of neighborhood-based methods in comparison to other models is not trivial.Cluster-based methods exhibit better scalability than neighborhood-based modeling

Anis Sharafoddini, Joel A Dubin, Joon Lee

JMIR Med Inform 2017;5(1):e7


The Impact of Implementation of a Clinically Integrated Problem-Based Neonatal Electronic Health Record on Documentation Metrics, Provider Satisfaction, and Hospital Reimbursement: A Quality Improvement Project

The Impact of Implementation of a Clinically Integrated Problem-Based Neonatal Electronic Health Record on Documentation Metrics, Provider Satisfaction, and Hospital Reimbursement: A Quality Improvement Project

We report the fiscal impact of improved documentation based on changes in expected APR-DRG-based hospital payments.MethodsBackgroundIn 2014-2015, all physician documentation at Lee Health in Fort Myers, FL, was transitioning from a dictation-based system to

William Liu, Thomas Walsh

JMIR Med Inform 2018;6(2):e40