Machine Learning Applications in Healthcare and Epidemiology
I apply my methodological research in hospitals, pharmaceutical companies, and organizations worldwide to create safe personalized treatments for pediatric patients, optimized clinical trials for life-saving vaccines, ,mitigation plans for governmental restrictions, and more.
2022
Data-Driven Vaccine Development with Janssen (with Bertsimas, D., Xu, J., Khan, N.) INFORMS Journal of Applied Analytics 53(1), 70-84. (INFORMS Edelman Award Finalist)
2021
Forecasting COVID-19 and Analyzing the Effect of Government Interventions (with Bouardi, H. T., Lami, O. S., Trikalinos, T. A., Trichakis, N. K., & Bertsimas, D.) Operations Research (2022). Ahead of Print.
2021
From predictions to prescriptions: A data-driven response to COVID-19 (with Bertsimas, D., Boussioux, L., Wright, R. C., Delarue, A., Digalakis Jr, V., Jacquillat, A., ... & Nohadani, O.) Health Care Management Science, 24(2), 253-272.
2021
Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States (with Cramer, E. Y., Ray, E. L., Lopez, V. K., Bracher, J., Brennen, A., Castro Rivadeneira, A. J., ... & Georgescu, A.). Proceedings of the National Academy of Sciences, 119(15), e2113561119.
2021
Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the US (with Ray, E. L., Wattanachit, N., Niemi, J., Kanji, A. H., House, K., Cramer, E. Y., ... & COVID-19 Forecast Hub Consortium.). MedRXiv (2020).
2021
Short-term forecasting of COVID-19 in Germany and Poland during the second wave – a preregistered study (with Bracher, J., Wolffram, D., Deuschel, J., Gorgen, J., Ketterer, J.L., et al). Nature Communications, 12(5173), (2021).
2021
Where to locate COVID-19 mass vaccination facilities? (with Bertsimas, D., Digalakis, V., Jacquillat, A., & Previero, A.). Naval Research Logistics (NRL) (2021).
2020
Prescriptive Analytics for Reducing 30-day Hospital Readmissions after General Surgery (with Bertsimas, D., Paschalidis, I. C., & Wang, T.). PloS one, 15(9), e0238118 (2020).
2020
Selecting Children with VUR Who are Most Likely to Benefit from Antibiotic Prophylaxis: Application of Machine Learning to RIVUR (with Wang, H. H. S., Li, M., Bertsimas, D., Estrada, C., & Caleb, N.). The Journal of Urology, 10-1097 (2020).
2019
Targeted Workup after Initial Febrile Urinary Tract Infection: Using a Novel Machine Learning Model to Identify Children Most Likely to Benefit from Voiding Cystourethrogram (part of Advanced Analytics Group of Pediatric Urology and ORC Personalized Medicine Group). The Journal of Urology, 202(1), 144-152 (2019).