Mazzulli, Tony

Federated learning for predicting clinical outcomes in patients with COVID-19

Dayan, I., Roth, H. R., Zhong, A., Harouni, A., Gentili, A., Abidin, A. Z., Liu, A., Costa, A. B., Wood, B. J., Tsai, C.-S., et al. (2021) · Nature Medicine

Machine Learning in HealthcareCOVID-19 diagnosis using AI

Cited by 842

A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America

Greninger, A. L., Chen, E. C., Sittler, T., Scheinerman, A., Roubinian, N., Yu, G., Kim, E., Pillai, D. R., Guyard, C., Mazzulli, T., et al. (2010) · PLoS ONE

Influenza Virus Research StudiesGenomics and Phylogenetic Studies

Cited by 193

Evaluation of the RealArt Malaria LC Real-Time PCR Assay for Malaria Diagnosis

Farcas, G. A., Zhong, K. J. Y., Mazzulli, T., & Kain, K. C. (2004) · Journal of Clinical Microbiology

Malaria Research and ControlTravel-related health issues

Cited by 87