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Michael Baiocchi
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2020 – today
- 2022
- [c4]Conor K. Corbin, Michael Baiocchi, Jonathan H. Chen:
How to Avoid Incorrect Clinical Machine Learning Model Performance Estimates When Class Labels Are Only Partially Observed. AMIA 2022 - [i1]Conor K. Corbin, Michael Baiocchi, Jonathan H. Chen:
Avoiding Biased Clinical Machine Learning Model Performance Estimates in the Presence of Label Selection. CoRR abs/2209.09188 (2022) - 2021
- [j1]Minh Nguyen, Conor K. Corbin, Tiffany Eulalio, Nicolai P. Ostberg, Gautam Machiraju, Ben J. Marafino, Michael Baiocchi, Christian Rose, Jonathan H. Chen:
Developing machine learning models to personalize care levels among emergency room patients for hospital admission. J. Am. Medical Informatics Assoc. 28(11): 2423-2432 (2021) - [c3]Andre Kumar, Rachael C. Aikens, Jason Horn, Lisa Shieh, Mark A. Musen, Michael Baiocchi, Russ B. Altman, Mary K. Goldstein, Steven M. Asch, Jonathan H. Chen:
Randomized user testing of recommender system clinical decision support. AMIA 2021 - [c2]Ben J. Marafino, Alejandro Schuler, Vincent X. Liu, Art B. Owen, Gabriel J. Escobar, Michael Baiocchi:
Integrating Evaluations of Predictive Algorithm-Driven Interventions into Clinical Workflows with the Dynamic Discontinuity Deployment Design. AMIA 2021 - [c1]Minh Nguyen, Nicolai P. Ostberg, Conor K. Corbin, Tiffany Eulalio, Gautam Machiraju, Ben J. Marafino, Michael Baiocchi, Christian Rose, Jonathan H. Chen:
Predicting Level of Care for Emergency Hospital Admissions to Optimize Triage. AMIA 2021
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