Search Results for author:
Found 9 papers, 1 papers with code
Self-supervision for health insurance claims data: a Covid-19 use case
In this work, we modify and apply self-supervision techniques to the domain of medical health insurance claims.
Identification of Pediatric Sepsis Subphenotypes for Enhanced Machine Learning Predictive Performance: A Latent Profile Analysis
Machine learning experiments comparing the predictive performance of models derived without training data profiling against profile targeted models suggest statistically significant improved performance of prediction can be obtained.
Combining Structured and Free-text Electronic Medical Record Data for Real-time Clinical Decision Support
The goal of this work is to utilize Electronic Medical Record (EMR) data for real-time Clinical Decision Support (CDS).
Using Latent Class Analysis to Identify ARDS Sub-phenotypes for Enhanced Machine Learning Predictive Performance
In this study, we integrate knowledge of the heterogeneity of ARDS patients into predictive model building.
Training and Prediction Data Discrepancies: Challenges of Text Classification with Noisy, Historical Data
Industry datasets used for text classification are rarely created for that purpose.
Semantically Enhanced Dynamic Bayesian Network for Detecting Sepsis Mortality Risk in ICU Patients with Infection
Although timely sepsis diagnosis and prompt interventions in Intensive Care Unit (ICU) patients are associated with reduced mortality, early clinical recognition is frequently impeded by non-specific signs of infection and failure to detect signs of sepsis-induced organ dysfunction in a constellation of dynamically changing physiological data.
