Gabriel Demuth
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View article: A Novel Alternating Joint Longitudinal Model for Post-ICU Hemoglobin Prediction
A Novel Alternating Joint Longitudinal Model for Post-ICU Hemoglobin Prediction Open
Anemia is common in patients post-ICU discharge. However, which patients will develop or recover from anemia remains unclear. Prediction of anemia in this population is complicated by hospital readmissions, which can have substantial impac…
View article: Impact of a machine learning algorithm on time to palliative care in a primary care population: protocol for a stepped-wedge pragmatic randomized trial
Impact of a machine learning algorithm on time to palliative care in a primary care population: protocol for a stepped-wedge pragmatic randomized trial Open
Background As primary care populations age, timely identification of palliative care need is becoming increasingly relevant. Previous studies have targeted particular patient populations with life-limiting disease, but few have focused on …
View article: Early Post-Hospitalization Hemoglobin Recovery and Clinical Outcomes in Survivors of Critical Illness: A Population-Based Cohort Study
Early Post-Hospitalization Hemoglobin Recovery and Clinical Outcomes in Survivors of Critical Illness: A Population-Based Cohort Study Open
Anemia is common during critical illness, is associated with adverse clinical outcomes, and often persists after hospitalization. The goal of this investigation is to assess the relationships between post-hospitalization hemoglobin recover…
View article: Assessment of Data Quality Variability across Two EHR Systems through a Case Study of Post-Surgical Complications
Assessment of Data Quality Variability across Two EHR Systems through a Case Study of Post-Surgical Complications Open
Translation of predictive modeling algorithms into routine clinical care workflows faces challenges in the form of varying data quality-related issues caused by the heterogeneity of electronic health record (EHR) systems. To better underst…
View article: Early Detection of Post-Surgical Complications using Time-series Electronic Health Records.
Early Detection of Post-Surgical Complications using Time-series Electronic Health Records. Open
Models predicting health complications are increasingly attempting to reflect the temporally changing nature of patient status. However, both the practice of medicine and electronic health records (EHR) have yet to provide a true longitudi…
View article: Quantifying the Importance of COVID-19 Vaccination to Our Future Outlook
Quantifying the Importance of COVID-19 Vaccination to Our Future Outlook Open
View article: A Hierarchical Bayesian Model for Stochastic Spatiotemporal SIR Modeling and Prediction of COVID-19 Cases and Hospitalizations
A Hierarchical Bayesian Model for Stochastic Spatiotemporal SIR Modeling and Prediction of COVID-19 Cases and Hospitalizations Open
Most COVID-19 predictive modeling efforts use statistical or mathematical models to predict national- and state-level COVID-19 cases or deaths in the future. These approaches assume parameters such as reproduction time, test positivity rat…
View article: Improving the delivery of palliative care through predictive modeling and healthcare informatics
Improving the delivery of palliative care through predictive modeling and healthcare informatics Open
Objective Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, many patients who could benefit from PC do not receive it early enough or at all. We sought …
View article: State space models for partially observed biological and agricultural data
State space models for partially observed biological and agricultural data Open
State space models are important tools for the analysis of biological data, and although relatively unexplored in the realm of agricultural data, can be used to great effect there as well. We consider cases where data on the underlying sys…