M. Draugelis

发表

A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

Corey Chivers, Michael Draugelis, Asaf Hanish, 2019, Critical care medicine.

Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic

Gary E. Weissman, Michael Z. Levy, Jason D. Christie, 2020, Annals of Internal Medicine.

Electronic Health Record Mortality Prediction Model for Targeted Palliative Care Among Hospitalized Medical Patients: a Pilot Quasi-experimental Study

Susan H. Regli, S. H. Regli, Corey Chivers, 2019, Journal of General Internal Medicine.

In response to "Development, implementation and impact of an automated early warning and response system for sepsis".

Corey Chivers, Michael Draugelis, Craig A Umscheid, 2015, Journal of hospital medicine.

The Good, The Bad, and The Ugly of Deploying and Adopting Machine Learning Based Models in Clinical Practice

Berkman Sahiner, David Holmes, Yin Aphinyanaphongs, 2017, AMIA.

Guiding Efficient, Effective, and Patient-Oriented Electrolyte Replacement in Critical Care: An Artificial Intelligence Reinforcement Learning Approach

B. Engelhardt, C. Hanson, K. Laudanski, 2022, Journal of personalized medicine.

A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units pdf

Barbara E. Engelhardt, Corey Chivers, Michael Draugelis, 2017, UAI.

Validation of a Machine Learning Algorithm to Predict 180-Day Mortality for Outpatients With Cancer.

S. H. Regli, Ravi B. Parikh, Jinbo Chen, 2020, JAMA oncology.

Why Is the Electronic Health Record So Challenging for Research and Clinical Care?

Charles E. Kahn, Jason W. Moore, T. Cook, 2021, Methods of Information in Medicine.

Forecasting PPE Consumption during a Pandemic: The Case of Covid-19

K. Lum, C. Terwiesch, J. Johndrow, 2020, medRxiv.

Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer

S. H. Regli, Ravi B. Parikh, Mitesh S. Patel, 2019, JAMA network open.

Evaluating equity in performance of an electronic health record-based 6-month mortality risk model to trigger palliative care consultation: a retrospective model validation analysis

S. Halpern, Stephanie Teeple, K. Linn, 2023, BMJ Quality & Safety.

Prospective validation of a machine learning algorithm to predict short-term mortality among outpatients with cancer.

Ravi B. Parikh, Mitesh S. Patel, A. Navathe, 2020 .

Application of machine learning approaches to administrative claims data to predict clinical outcomes in medical and surgical patient populations

M. D. Stubna, Emily J. Mackay, N. Desai, 2021, PloS one.

Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

Michael Draugelis, P. J. Donnelly, Craig A Umscheid, 2019, Critical care medicine.

Remote Monitoring of Critically-Ill Post-Surgical Patients: Lessons from a Biosensor Implementation Trial

C. Hanson, K. Laudanski, M. Draugelis, 2021, Healthcare.

Sparse multi-output Gaussian processes for online medical time series prediction

Kai Li, Gregory Darnell, Li-Fang Cheng, 2020, BMC Medical Informatics and Decision Making.

Clinical Impact of an Electronic Dashboard and Alert System for Sedation Minimization and Ventilator Liberation: A Before-After Study

Shivan J. Mehta, A. Gabrielli, B. Fuchs, 2019, Critical care explorations.