Ruppert, Matthew M.

Comparing clinical judgment with the MySurgeryRisk algorithm for preoperative risk assessment: a pilot usability study.

Brennan, M., Puri, S., Ozrazgat-Baslanti, T., Feng, Z., Ruppert, M., Hashemighouchani, H., Momcilovic, P., Li, X., Wang, D. Z., & Bihorac, A. (2019) · Surgery

Artificial Intelligence in Healthcare and EducationElectronic Health Records Systems

Cited by 131

Improved predictive models for acute kidney injury with IDEA: Intraoperative Data Embedded Analytics.

Adhikari, L., Ozrazgat-Baslanti, T., Ruppert, M., Madushani, R. W. M. A., Paliwal, S., Hashemighouchani, H., Zheng, F., Tao, M., Lopes, J. M., Li, X., et al. (2019) · PLOS ONE

Acute Kidney Injury ResearchArtificial Intelligence in Healthcare

Cited by 98

Improving the Intensive Care Patient Experience With Virtual Reality—A Feasibility Study

Ong, T. L., Ruppert, M. M., Akbar, M., Rashidi, P., Ozrazgat-Baslanti, T., Bihorac, A., & Suvajdzic, M. (2020) · Critical Care Explorations

Intensive Care Unit Cognitive DisordersVirtual Reality Applications and Impacts

Cited by 80

Uncertainty-aware deep learning in healthcare: A scoping review

Loftus, T. J., Shickel, B., Ruppert, M. M., Balch, J. A., Ozrazgat-Baslanti, T., Tighe, P. J., Efron, P. A., Hogan, W. R., Rashidi, P., Upchurch, G. R., et al. (2022) · PLOS Digital Health

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 73

Predictive Modeling for Readmission to Intensive Care: A Systematic Review

Ruppert, M. M., Loftus, T. J., Small, C., Li, H., Ozrazgat-Baslanti, T., Balch, J., Holmes, R., Tighe, P. J., Upchurch, G. R., Efron, P. A., et al. (2023) · Critical Care Explorations

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 24

Deep Multi-Modal Transfer Learning for Augmented Patient Acuity Assessment in the Intelligent ICU

Shickel, B., Davoudi, A., Ozrazgat-Baslanti, T., Ruppert, M., Bihorac, A., & Rashidi, P. (2021) · Frontiers in Digital Health

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 21

Physiologic signatures within six hours of hospitalization identify acute illness phenotypes

Ren, Y., Loftus, T. J., Li, Y., Guan, Z., Ruppert, M. M., Datta, S., Upchurch, G. R., Tighe, P. J., Rashidi, P., Shickel, B., et al. (2022) · PLOS Digital Health

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 6