EricKOermannMD

Assistant Professor

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Office
530 1st Ave
# SKI8S
New York, NY 10016
Phone+1 646-501-0397

Fax+1 212-263-8042

Background in mathematics (differential geometry), machine learning, bioethics, and genetics. More recently have worked on machine learning with clinical datasets, predicting survival, medical informatics, stereotactic radiosurgery, and minimally invasive neurosurgical approaches.
Currently interested in: deep learning, survival, neural implants, radiomics, artificial intelligence.

Icahn School of Medicine at Mount SinaiResidency, Neurological Surgery, 2013 - 2020
Icahn School of Medicine at Mount SinaiResidency, Neurological Surgery, 2012 - 2019
Georgetown University School of MedicineClass of 2013

30 Under 30 in Healthcare Forbes, 2015
2015 AANS Annual Meeting: Cerebrovascular First Place Eposter Award American Association of Neurological Surgeons, 2015
The Stacy L. Rollins, Jr., MD Award for outstanding academic performance. Georgetown University Department of Neurosurgery., 2013
The Excellence in Education and Research Award for outstanding academic performance Georgetown University Department of Radiation Medicine, 2013
Doris Duke Clinical Research Fellowship Doris Duke Charitable Research Foundation, 2011-2012
Summer Medical Student Fellowship American Brain Tumor Association, 2009
Pi Epsilon Mu – National Mathematics Honor Society Pi Epsilon Mu, 2008
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PubMed

77 citations
Natural Language-based Machine Learning Models for the Annotation of Clinical Radiology Reports.
John R. Zech, Margaret Pain, Joseph J. Titano, Marcus A. Badgeley, Javin Schefflein
Radiology. 2018-01-30
69 citations
Predicting Trends in Cervical Spinal Surgery in the United States from 2020 to 2040.
Sean N Neifert, Michael L Martini, Frank J. Yuk, Ian T McNeill, John M. Caridi
World Neurosurgery. 2020-05-19
3 citations
Federated AI, Current State, and Future Potential.
Phoebe Clark, Eric K Oermann, Dinah Chen, Lama A Al-Aswad
Asia-Pacific Journal of Ophthalmology. 2023-05-31

Journal Articles

Variable Generalization Performance of a Deep Learning Model to Detect Pneumonia in Chest Radiographs: A Cross-Sectional Study
Eric Oermann, MD, PLoS One
Automated Deep-Neural-Network Surveillance of Cranial Images for Acute Neurologic Events
Margaret Pain, J Mocco, Javin Schefflein, Burton Drayer, Joseph J Titano, Samuel Cho, Marcus Badgeley, Michael Cai, Joshua Bederson, Eric K Oermann, Nature

Artificial Intelligence Meets the World’s Largest Database of Brain ScansApril 25th, 2023
PCPs ‘First Line’ of Defense Against Projected Increase in Neurological DisordersAugust 13th, 2020
Artificial Intelligence in Medical DevicesDecember 2nd, 2018
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