Michael Draugelis

Geisinger Medical Center — United States

Computer Science · Physical Sciences

11h-index1.4kcitations28works0.52yr avg
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Research Topics

Machine Learning in Healthcare(8), Palliative Care and End-of-Life Issues(6), Sepsis Diagnosis and Treatment(5), Artificial Intelligence in Healthcare and Education(4), Global Cancer Incidence and Screening(3)

Publications28 total

Correction: Eliminating the AI digital divide by building local capacity
PLOS Digital Health·2025Open Access
Eliminating the AI digital divide by building local capacity
PLOS Digital Health·2025· 1 citedOpen Access
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
BMJ Quality & Safety·2023· 7 citedOpen Access
Guiding Efficient, Effective, and Patient-Oriented Electrolyte Replacement in Critical Care: An Artificial Intelligence Reinforcement Learning Approach
Journal of Personalized Medicine·2022· 7 citedOpen Access
Application of machine learning approaches to administrative claims data to predict clinical outcomes in medical and surgical patient populations
PLoS ONE·2021· 32 citedOpen Access
Augmenting machine learning algorithms to predict mortality using patient-reported outcomes in oncology.
Journal of Clinical Oncology·2021
Why Is the Electronic Health Record So Challenging for Research and Clinical Care?
Methods of Information in Medicine·2021· 98 citedOpen Access
Remote Monitoring of Critically-Ill Post-Surgical Patients: Lessons from a Biosensor Implementation Trial
Healthcare·2021· 6 citedOpen Access
Validation of a Machine Learning Algorithm to Predict 180-Day Mortality for Outpatients With Cancer
JAMA Oncology·2020· 115 citedOpen Access
Forecasting PPE Consumption during a Pandemic: The Case of Covid-19
2020· 8 citedOpen Access
Sparse multi-output Gaussian processes for online medical time series prediction
BMC Medical Informatics and Decision Making·2020· 67 citedOpen Access
Electronically Triggered Hospital-Based Palliative Care: Patient and Clinician Perspectives (RP509)
Journal of Pain and Symptom Management·2020
Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes.
International Conference on Artificial Intelligence and Statistics·2020
Prospective validation of a machine learning algorithm to predict short-term mortality among outpatients with cancer.
Journal of Clinical Oncology·2020· 3 cited
Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic
Annals of Internal Medicine·2020· 310 cited
1298: ARE BIOSENSORS TRULY READY FOR PRIME-TIME INTRODUCTION? LESSON FROM AN ICU IMPLEMENTATION TRIAL
Critical Care Medicine·2019
Derivation and implementation of a machine learning approach to prompt serious illness conversations among outpatients with cancer.
Journal of Clinical Oncology·2019· 2 cited
Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer
JAMA Network Open·2019· 219 citedOpen Access
A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice*
Critical Care Medicine·2019· 248 citedOpen Access
Electronic Health Record Mortality Prediction Model for Targeted Palliative Care Among Hospitalized Medical Patients: a Pilot Quasi-experimental Study
Journal of General Internal Medicine·2019· 74 citedOpen Access
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Frequent Co-authors

Corey Chivers(19), Nina O’Connor(7), Ravi B. Parikh(6), Susan Harkness Regli(6), Barbara E. Engelhardt(6), Lawrence N. Shulman(5), Asaf Hanish(4), C. William Hanson(4), Jennifer Braun(4), Lynn M. Schuchter(4), Mitesh S. Patel(4), Justin E. Bekelman(4), Bianca Dumitrascu(4), Lifang Cheng(4), Gary E. Weissman(3), Scott D. Halpern(3), Barry D. Fuchs(3), Craig A. Umscheid(3), Amol S. Navathe(3), Yijie Liu(3)