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Applications in
Healthcare

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.

2024

A machine learning algorithm predicting risk of dilating VUR among infants with hydronephrosis using UTD classification (with Wang, H. H. S., Li, M., Cahill, D., Panagides, J., Logvinenko, T., Chow, J., & Nelson, C.) Journal of Pediatric Urology, 20(2), 271-278.

2024

Benchmarking large language models on cmexam-a comprehensive chinese medical exam dataset (with Liu, J., Zhou, P., Hua, Y., Chong, D., Tian, Z., Liu, A....) Advances in Neural Information Processing Systems 36 (2024).

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). 

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

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).

Contact
Information

Technology & Operations Management, 
Harvard Business School

Morgan Hall, Soldiers Field
Boston, MA 02163

mili at hbs dot edu (Academic)

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©2023 by Michael Lingzhi Li

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