Shieh, Lisa

Surviving Sepsis Campaign: International guidelines for management of sepsis and septic shock: 2016.

Rhodes, A., Evans, L. E., Alhazzani, W., Levy, M. M., Antonelli, M., Ferrer, R., Kumar, A., Sevransky, J. E., Sprung, C. L., Nunnally, M. E., et al. (2017) · Intensive Care Medicine

Sepsis Diagnosis and TreatmentAbdominal Surgery and Complications

Cited by 6,621

Surviving Sepsis Campaign: International guidelines for management of sepsis and septic shock: 2016.

Rhodes, A., Evans, L. E., Alhazzani, W., Levy, M. M., Antonelli, M., Ferrer, R., Kumar, A., Sevransky, J. E., Sprung, C. L., Nunnally, M. E., et al. (2017) · Critical Care Medicine

Sepsis Diagnosis and TreatmentAbdominal Surgery and Complications

Cited by 3,652

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach

Desautels, T., Calvert, J., Hoffman, J., Jay, M., Kerem, Y., Shieh, L., Shimabukuro, D., Chettipally, U., Feldman, M. D., Barton, C., et al. (2016) · JMIR Medical Informatics

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 509

Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU

Mao, Q., Jay, M., Hoffman, J. L., Calvert, J., Barton, C., Shimabukuro, D., Shieh, L., Chettipally, U., Fletcher, G., Kerem, Y., et al. (2018) · BMJ Open

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 336

Electronic health record-based clinical decision support alert for severe sepsis: A randomised evaluation.

Downing, N. L., Rolnick, J., Poole, S. F., Hall, E., Wessels, A. J., Heidenreich, P., & Shieh, L. (2019) · BMJ Quality & Safety

Sepsis Diagnosis and TreatmentElectronic Health Records Systems

Cited by 112

Effectiveness of an Artificial Intelligence–Enabled Intervention for Detecting Clinical Deterioration

Gallo, R. J., Shieh, L., Smith, M., Marafino, B. J., Geldsetzer, P., Asch, S. M., Shum, K., Lin, S., Westphal, J., Hong, G., et al. (2024) · JAMA Internal Medicine

Healthcare Technology and Patient MonitoringMachine Learning in Healthcare

Cited by 58

Targeting repetitive laboratory testing with electronic health records-embedded predictive decision support: A pre-implementation study

Rabbani, N., Ma, S. P., Li, R. C., Winget, M., Weber, S., Boosi, S., Pham, T. D., Svec, D., Shieh, L., & Chen, J. H. (2023) · Clinical Biochemistry

Electronic Health Records SystemsHealthcare cost, quality, practices

Cited by 20

Examining Diversity in Digital Therapeutics Clinical Trials: Descriptive Analysis

Adu-Brimpong, J., Pugh, J., Darko, D. A., & Shieh, L. (2023) · Journal of Medical Internet Research

Ethics in Clinical ResearchDigital Mental Health Interventions

Cited by 13

SmartAlert: Integrating Machine Learning and Alert Triggers into Live Electronic Medical Record Systems, Targeting Low-Yield Inpatient Lab Tests

Jiang, Y., Ma, S. P., Liang, A. S., Kim, G., Acharya, A., Mony, S., Punnathanam, S., Makeown, J., Jose, J., Shieh, L., et al. (2026) · medRxiv

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 1

SmartAlert - Implementing Machine Learning-Driven Clinical Decision Support for Inpatient Laboratory Utilization Reduction

Liang, A. S., Amrollahi, F., Jiang, Y., Corbin, C. K., Kim, G. Y. E., Mui, D., Crowell, T., Acharya, A., Mony, S., Punnathanam, S., et al. (2026) · NEJM AI

Electronic Health Records SystemsArtificial Intelligence in Healthcare and Education

Cited by 0