Article Versions Notes

Beltrami AP, De Martino M, Dalla E, Malfatti MC, Caponnetto F, Codrich M, Stefanizzi D, Fabris M, Sozio E, D’Aurizio F, et al. Combining Deep Phenotyping of Serum Proteomics and Clinical Data via Machine Learning for COVID-19 Biomarker Discovery. International Journal of Molecular Sciences. 2022; 23(16):9161. https://doi.org/10.3390/ijms23169161

Beltrami, Antonio Paolo, Maria De Martino, Emiliano Dalla, Matilde Clarissa Malfatti, Federica Caponnetto, Marta Codrich, Daniele Stefanizzi, Martina Fabris, Emanuela Sozio, Federica D’Aurizio, and et al. 2022. "Combining Deep Phenotyping of Serum Proteomics and Clinical Data via Machine Learning for COVID-19 Biomarker Discovery" International Journal of Molecular Sciences 23, no. 16: 9161. https://doi.org/10.3390/ijms23169161

Beltrami, A. P., De Martino, M., Dalla, E., Malfatti, M. C., Caponnetto, F., Codrich, M., Stefanizzi, D., Fabris, M., Sozio, E., D’Aurizio, F., Pucillo, C. E. M., Sechi, L. A., Tascini, C., Curcio, F., Foresti, G. L., Piciarelli, C., De Nardin, A., Tell, G., & Isola, M. (2022). Combining Deep Phenotyping of Serum Proteomics and Clinical Data via Machine Learning for COVID-19 Biomarker Discovery. International Journal of Molecular Sciences, 23(16), 9161. https://doi.org/10.3390/ijms23169161