Fuchs, Barry D.

A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice*

Giannini, H. M., Ginestra, J. C., Chivers, C., Draugelis, M., Hanish, A., Schweickert, W. D., Fuchs, B. D., Meadows, L., Lynch, M., Donnelly, P. J., et al. (2019) · Critical Care Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 269

Clinician perception of a machine learning–based early warning system designed to predict severe sepsis and septic shock

Ginestra, J. C., Giannini, H. M., Schweickert, W. D., Meadows, L., Lynch, M. J., Pavan, K., Chivers, C. J., Draugelis, M., Donnelly, P. J., Fuchs, B. D., et al. (2019) · Critical Care Medicine

Sepsis Diagnosis and TreatmentHealthcare Technology and Patient Monitoring

Cited by 159

Severe sepsis cohorts derived from claims-based strategies appear to be biased toward a more severely ill patient population.

Whittaker, S.-A., Mikkelsen, M. E., Gaieski, D. F., Koshy, S., Kean, C., & Fuchs, B. D. (2013) · Critical Care Medicine

Sepsis Diagnosis and TreatmentMedical Coding and Health Information

Cited by 156

Post-acute care use and hospital readmission after sepsis.

Jones, T. K., Fuchs, B. D., Small, D. S., Halpern, S. D., Hanish, A., Umscheid, C. A., Baillie, C. A., Kerlin, M. P., Gaieski, D. F., & Mikkelsen, M. E. (2015) · Annals of the American Thoracic Society

Sepsis Diagnosis and TreatmentHospital Admissions and Outcomes

Cited by 140

Characteristics, Outcomes, and Trends of Patients With COVID-19–Related Critical Illness at a Learning Health System in the United States

Anesi, G. L., Jablonski, J., Harhay, M. O., Atkins, J. H., Bajaj, J., Baston, C., Brennan, P. J., Candeloro, C. L., Catalano, L. M., Cereda, M. F., et al. (2021) · Annals of Internal Medicine

COVID-19 Clinical Research StudiesRespiratory Support and Mechanisms

Cited by 115

Hospital-based acute care use in survivors of septic shock.

Ortego, A., Gaieski, D. F., Fuchs, B. D., Jones, T., Halpern, S. D., Small, D. S., Sante, S. C., Drumheller, B., Christie, J. D., & Mikkelsen, M. E. (2015) · Critical Care Medicine

Sepsis Diagnosis and TreatmentEmergency and Acute Care Studies

Cited by 67

Clinician Perception of the Effectiveness of an Automated Early Warning and Response System for Sepsis in an Academic Medical Center

Guidi, J. L., Clark, K., Upton, M. T., Faust, H., Umscheid, C. A., Lane-Fall, M. B., Mikkelsen, M. E., Schweickert, W. D., Vanzandbergen, C. A., Betesh, J., et al. (2015) · Annals of the American Thoracic Society

Sepsis Diagnosis and TreatmentHealthcare Technology and Patient Monitoring

Cited by 43

Natural language processing to assess documentation of features of critical illness in discharge documents of acute respiratory distress syndrome survivors.

Weissman, G. E., Harhay, M. O., Lugo, R. M., Fuchs, B. D., Halpern, S. D., & Mikkelsen, M. E. (2016) · Annals of the American Thoracic Society

Nursing Diagnosis and DocumentationMedical Coding and Health Information

Cited by 35