Adhikari, Lasith

Analysis of Discrepancies between Pulse Oximetry and Arterial Oxygen Saturation Measurements by Race and Ethnicity and Association with Organ Dysfunction and Mortality

Wong, A.-K. I., Charpignon, M., Kim, H., Josef, C., de Hond, A. A. H., Fojas, J. J., Tabaie, A., Liu, X., Mireles-Cabodevila, E., Carvalho, L., et al. (2021) · JAMA Network Open

Non-Invasive Vital Sign MonitoringHemodynamic Monitoring and Therapy

Cited by 268

DeepSOFA: a continuous acuity score for critically ill patients using clinically interpretable deep learning.

Shickel, B., Loftus, T. J., Adhikari, L., Ozrazgat-Baslanti, T., Bihorac, A., & Rashidi, P. (2019) · Scientific Reports

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 165

Systematic Review and Comparison of Publicly Available ICU Data Sets—A Decision Guide for Clinicians and Data Scientists

Sauer, C. M., Dam, T. A., Celi, L. A., Faltys, M., de la Hoz, M. A. A., Adhikari, L., Ziesemer, K. A., Girbes, A., Thoral, P. J., & Elbers, P. (2022) · Critical Care Medicine

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 104

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