Churpek, Matthew M.

Quick sepsis-related organ failure assessment, systemic inflammatory response syndrome, and early warning scores for detecting clinical deterioration in infected patients outside the intensive care unit

Churpek, M. M., Snyder, A., Han, X., Sokol, S., Pettit, N., Howell, M. D., & Edelson, D. P. (2017) · American Journal of Respiratory and Critical Care Medicine

Sepsis Diagnosis and TreatmentInflammation biomarkers and pathways

Cited by 689

Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards

Churpek, M. M., Yuen, T. C., Winslow, C., Meltzer, D. O., Kattan, M. W., & Edelson, D. P. (2016) · Critical Care Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 638

The development of a machine learning inpatient acute kidney injury prediction model.

Koyner, J. L., Carey, K. A., Edelson, D. P., & Churpek, M. M. (2018) · Critical Care Medicine

Acute Kidney Injury ResearchMachine Learning in Healthcare

Cited by 323

Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example*

Thoral, P. J., Peppink, J. M., Driessen, R. H., Sijbrands, E. J. G., Kompanje, E. J. O., Kaplan, L., Bailey, H., Kesecioglu, J., Cecconi, M., Churpek, M., et al. (2021) · Critical Care Medicine

Privacy-Preserving Technologies in DataElectronic Health Records Systems

Cited by 257

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

Association between intensive care unit transfer delay and hospital mortality: A multicenter investigation

Churpek, M. M., Wendlandt, B., Zadravecz, F. J., Adhikari, R., Winslow, C., & Edelson, D. P. (2016) · Journal of Hospital Medicine

Cardiac Arrest and ResuscitationSepsis Diagnosis and Treatment

Cited by 143

Identifying Patients With Sepsis on the Hospital Wards

Bhattacharjee, P., Edelson, D. P., & Churpek, M. M. (2017) · Chest

Sepsis Diagnosis and TreatmentInflammation biomarkers and pathways

Cited by 120

Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups

Thompson, H. M., Sharma, B., Bhalla, S., Boley, R., McCluskey, C., Dligach, D., Churpek, M. M., Karnik, N. S., & Afshar, M. (2021) · Journal of the American Medical Informatics Association

Ethics and Social Impacts of AIMachine Learning in Healthcare

Cited by 78

The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial

Winslow, C. J., Edelson, D. P., Churpek, M. M., Taneja, M., Shah, N. S., Datta, A., Wang, C.-H., Ravichandran, U., McNulty, P., Kharasch, M., et al. (2022) · Critical Care Medicine

Cardiac Arrest and ResuscitationMachine Learning in Healthcare

Cited by 69

Real-Time Risk Prediction on the Wards: A Feasibility Study

Kang, M. A., Churpek, M. M., Zadravecz, F. J., Adhikari, R., Twu, N. M., & Edelson, D. P. (2016) · Critical Care Medicine

Cardiac Arrest and ResuscitationHealthcare Technology and Patient Monitoring

Cited by 61

Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): A retrospective deep learning study

Afshar, M., Sharma, B., Dligach, D., Oguss, M., Brown, R., Chhabra, N., Thompson, H. M., Markossian, T., Joyce, C., Churpek, M. M., et al. (2022) · The Lancet Digital Health

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 55

Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults

Afshar, M., Adelaine, S., Resnik, F., Mundt, M. P., Long, J., Leaf, M., Ampian, T., Wills, G. J., Schnapp, B., Chao, M., et al. (2023) · JMIR Medical Informatics

Electronic Health Records SystemsMachine Learning in Healthcare

Cited by 44

Individualized Treatment Effects of Bougie versus Stylet for Tracheal Intubation in Critical Illness

Seitz, K. P., Spicer, A. B., Casey, J. D., Buell, K. G., Qian, E. T., Graham Linck, E. J., Driver, B. E., Self, W. H., Ginde, A. A., Trent, S. A., et al. (2023) · American Journal of Respiratory and Critical Care Medicine

Airway Management and Intubation TechniquesRespiratory Support and Mechanisms

Cited by 32

A scoping review of publicly available language tasks in clinical natural language processing

Gao, Y., Dligach, D., Christensen, L., Tesch, S., Laffin, R., Xu, D., Miller, T., Uzuner, O., Churpek, M. M., & Afshar, M. (2022) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 28

Automating Evaluation of AI Text Generation in Healthcare with a Large Language Model (LLM)-as-a-Judge

Croxford, E., Gao, Y., First, E., Pellegrino, N., Schnier, M., Caskey, J., Oguss, M., Wills, G., Chen, G., Dligach, D., et al. (2025) · medRxiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 25

Obstructive sleep apnea and adverse outcomes in surgical and nonsurgical patients on the wards

Lyons, P. G., Zadravecz, F. J., Edelson, D. P., Mokhlesi, B., & Churpek, M. M. (2015) · Journal of Hospital Medicine

Obstructive Sleep Apnea ResearchCardiac, Anesthesia and Surgical Outcomes

Cited by 25

The Precision Resuscitation With Crystalloids in Sepsis (PRECISE) Trial: A Trial Protocol

Bhavani, S. V., Holder, A., Miltz, D., Kamaleswaran, R., Khan, S., Easley, K., Murphy, D. J., Franks, N., Wright, D. W., Kraft, C., et al. (2024) · JAMA Network Open

Sepsis Diagnosis and TreatmentAcute Kidney Injury Research

Cited by 21

Multicenter Development and Validation of a Multimodal Deep Learning Model to Predict Moderate to Severe AKI

Koyner, J. L., Martin, J., Carey, K. A., Caskey, J., Edelson, D. P., Mayampurath, A., Dligach, D., Afshar, M., & Churpek, M. M. (2025) · Clinical Journal of the American Society of Nephrology

Acute Kidney Injury ResearchMachine Learning in Healthcare

Cited by 10

When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?

Gao, Y., Myers, S., Chen, S., Dligach, D., Miller, T. A., Bitterman, D., Churpek, M., & Afshar, M. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 8

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models

Gao, J., Chen, G., O’Rourke, A. P., Caskey, J., Carey, K. A., Oguss, M., Stey, A., Dligach, D., Miller, T., Mayampurath, A., et al. (2024) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 5

MoMA: a mixture-of-multimodal-agents architecture for enhancing clinical prediction modelling

Gao, J., Rahman, M., Caskey, J., Oguss, M., O’Rourke, A., Brown, R., Stey, A., Mayampurath, A., Churpek, M. M., Chen, G., et al. (2025) · npj Digital Medicine

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 2