bc. C. da Silva Lourenço (Catarina)


Medicine & Life Sciences
Deep Learning
Heart Arrest
Machine Learning
Engineering & Materials Science
Deep Learning


ISARIC Clinical Characterisation Group (2023). Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19. International journal of epidemiology, 52(2), 355-376. https://doi.org/10.1093/ije/dyad012
Wainstein, M., Spyrison, N., Dai, D., Ghadimi, M., Chávez-Iñiguez, J. S., Claure-Del Granado, R. , Brusse-Keizer, M. , Haalboom, M. , Nguyen, D. , Silva, C. , van der Palen, J. , Vonkeman, H., & ISARIC Characterization Group (2023). Association of Country Income Level With the Characteristics and Outcomes of Critically Ill Patients Hospitalized With Acute Kidney Injury and COVID-19. Kidney International Reports, 8(8), 1514-1530. https://doi.org/10.1016/j.ekir.2023.05.015
da Silva Lourenço, C. (2023). Deep Learning for EEG Analysis. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036556910
Reyes, L. F., Murthy, S., Garcia-Gallo, E., Merson, L., Ibáñez-Prada, E. D., Rello, J., Fuentes, Y. V., Martin-Loeches, I., Bozza, F., Duque, S., Taccone, F. S., Fowler, R. A., Kartsonaki, C., Gonçalves, B. P., Citarella, B. W., Aryal, D., Burhan, E., Cummings, M. J., Delmas, C., ... the ISARIC Characterization Group (2022). Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study. Critical care, 26(1), Article 276. https://doi.org/10.1186/s13054-022-04155-1
Garcia-Gallo, E., Merson, L., Kennon, K., Kelly, S., Citarella, B. W., Fryer, D. V., Shrapnel, S., Lee, J., Duque, S., Fuentes, Y. V., Balan, V., Smith, S., Wei, J., Gonçalves, B. P., Russell, C. D., Sigfrid, L., Dagens, A., Olliaro, P. L., Baruch, J., ... The Western Australian COVID-19 Research Response (2022). ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19. Scientific Data, 9(1), Article 454. https://doi.org/10.1038/s41597-022-01534-9

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University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands

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University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands