Deniz Vurmaz - Academia.edu (original) (raw)

Deniz Vurmaz

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Papers by Deniz Vurmaz

Research paper thumbnail of Nanometer Scale Surface Protein Patterns for Spatially Controlled Cell Adhesion

Research paper thumbnail of Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19

Lab on a Chip

The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a stati... more The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality.

Research paper thumbnail of Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation

Journal of Medical Internet Research

Background The coronavirus disease (COVID-19) pandemic has resulted in significant morbidity and ... more Background The coronavirus disease (COVID-19) pandemic has resulted in significant morbidity and mortality; large numbers of patients require intensive care, which is placing strain on health care systems worldwide. There is an urgent need for a COVID-19 disease severity assessment that can assist in patient triage and resource allocation for patients at risk for severe disease. Objective The goal of this study was to develop, validate, and scale a clinical decision support system and mobile app to assist in COVID-19 severity assessment, management, and care. Methods Model training data from 701 patients with COVID-19 were collected across practices within the Family Health Centers network at New York University Langone Health. A two-tiered model was developed. Tier 1 uses easily available, nonlaboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts the probability of mortality using biomarker measurements (C-reactive pro...

Research paper thumbnail of Nanometer Scale Surface Protein Patterns for Spatially Controlled Cell Adhesion

Research paper thumbnail of Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19

Lab on a Chip

The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a stati... more The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality.

Research paper thumbnail of Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation

Journal of Medical Internet Research

Background The coronavirus disease (COVID-19) pandemic has resulted in significant morbidity and ... more Background The coronavirus disease (COVID-19) pandemic has resulted in significant morbidity and mortality; large numbers of patients require intensive care, which is placing strain on health care systems worldwide. There is an urgent need for a COVID-19 disease severity assessment that can assist in patient triage and resource allocation for patients at risk for severe disease. Objective The goal of this study was to develop, validate, and scale a clinical decision support system and mobile app to assist in COVID-19 severity assessment, management, and care. Methods Model training data from 701 patients with COVID-19 were collected across practices within the Family Health Centers network at New York University Langone Health. A two-tiered model was developed. Tier 1 uses easily available, nonlaboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts the probability of mortality using biomarker measurements (C-reactive pro...

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