Bihorac, Azra

Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis

Shickel, B., Tighe, P. J., Bihorac, A., & Rashidi, P. (2018) · IEEE Journal of Biomedical and Health Informatics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 1,688

Acute kidney disease and renal recovery: consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup

16., O. B. O. T. A. D. Q. I. W., Chawla, L. S., Bellomo, R., Bihorac, A., Goldstein, S. L., Siew, E. D., Bagshaw, S. M., Bittleman, D., Cruz, D., Endre, Z., et al. (2017) · Nature Reviews Nephrology

Acute Kidney Injury ResearchChronic Kidney Disease and Diabetes

Cited by 1,537

Persistent inflammation and immunosuppression: A common syndrome and new horizon for surgical intensive care

Gentile, L. F., Cuenca, A. G., Efron, P. A., Ang, D., Bihorac, A., McKinley, B. A., Moldawer, L. L., & Moore, F. A. (2012) · Journal of Trauma and Acute Care Surgery

Sepsis Diagnosis and TreatmentClinical Nutrition and Gastroenterology

Cited by 801

Artificial Intelligence and Surgical Decision-making.

Loftus, T. J., Tighe, P. J., Filiberto, A. C., Efron, P. A., Brakenridge, S. C., Mohr, A. M., Rashidi, P., Upchurch, G. R., & Bihorac, A. (2020) · JAMA Surgery

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 650

Recovery after Acute Kidney Injury

Kellum, J. A., Sileanu, F. E., Bihorac, A., Hoste, E. A. J., & Chawla, L. S. (2017) · American Journal of Respiratory and Critical Care Medicine

Acute Kidney Injury ResearchChronic Kidney Disease and Diabetes

Cited by 520

MySurgeryRisk: development and validation of a machine-learning risk algorithm for major complications and death after surgery.

Bihorac, A., Ozrazgat-Baslanti, T., Ebadi, A., Motaei, A., Madkour, M., Pardalos, P. M., Lipori, G., Hogan, W. R., Efron, P. A., Moore, F., et al. (2019) · Annals of Surgery

Cardiac, Anesthesia and Surgical OutcomesMachine Learning in Healthcare

Cited by 377

Human Activity Recognition Using Inertial, Physiological and Environmental Sensors: A Comprehensive Survey

Demrozi, F., Pravadelli, G., Bihorac, A., & Rashidi, P. (2020) · IEEE Access

Context-Aware Activity Recognition SystemsGait Recognition and Analysis

Cited by 368

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

Innate Immunity in the Persistent Inflammation, Immunosuppression, and Catabolism Syndrome and Its Implications for Therapy

Horiguchi, H., Loftus, T. J., Hawkins, R. B., Raymond, S. L., Stortz, J. A., Hollen, M. K., Weiss, B. P., Miller, E. S., Bihorac, A., Larson, S. D., et al. (2018) · Frontiers in Immunology

Sepsis Diagnosis and TreatmentInflammation biomarkers and pathways

Cited by 164

Use of artificial intelligence in critical care: opportunities and obstacles

Pinsky, M. R., Bedoya, A., Bihorac, A., Celi, L., Churpek, M., Economou-Zavlanos, N. J., Elbers, P., Saria, S., Liu, V., Lyons, P. G., et al. (2024) · Critical Care

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 160

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

Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.

Cecconi, M., Greco, M., Shickel, B., Angus, D. C., Bailey, H., Bignami, E., Calandra, T., Celi, L. A., Einav, S., Elbers, P., et al. (2025) · Critical Care

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 80

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

Equity and Artificial Intelligence in Surgical Care

Johnson-Mann, C. N., Loftus, T. J., & Bihorac, A. (2021) · JAMA Surgery

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 44

Machine Learning Applications in Solid Organ Transplantation and Related Complications

Balch, J. A., Delitto, D., Tighe, P. J., Zarrinpar, A., Efron, P. A., Rashidi, P., Upchurch, G. R., Bihorac, A., & Loftus, T. J. (2021) · Frontiers in Immunology

Artificial Intelligence in Healthcare and EducationTransplantation: Methods and Outcomes

Cited by 33

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

Promoting AI Competencies for Medical Students: A Scoping Review on Frameworks, Programs, and Tools

Ma, Y., Song, Y., Balch, J. A., Ren, Y., Vellanki, D., Hu, Z., Brennan, M., Kolla, S., Guan, Z., Armfield, B., et al. (2024) · arXiv

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 16

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