6 citations · 10 across the 3 of their papers we have counts for
3 papers
stat.ML2019
Identification of Pediatric Sepsis Subphenotypes for Enhanced Machine Learning Predictive Performance: A Latent Profile Analysis
Tom Velez, Tony Wang, Ioannis Koutroulis +5
Background: While machine learning (ML) models are rapidly emerging as promising screening tools in critical care medicine, the identification of homogeneous subphenotypes within p…
cs.LG2019★ 4 cited
Using Latent Class Analysis to Identify ARDS Sub-phenotypes for Enhanced Machine Learning Predictive Performance
Tony Wang, Tim Tschampel, Emilia Apostolova +1
In this work, we utilize Machine Learning for early recognition of patients at high risk of acute respiratory distress syndrome (ARDS), which is critical for successful prevention…
cs.LG2018★ 6 cited
Semantically Enhanced Dynamic Bayesian Network for Detecting Sepsis Mortality Risk in ICU Patients with Infection
Tony Wang, Tom Velez, Emilia Apostolova +3
Although timely sepsis diagnosis and prompt interventions in Intensive Care Unit (ICU) patients are associated with reduced mortality, early clinical recognition is frequently impe…