2020
Comment on: British Society for Rheumatology guideline on diagnosis and treatment of giant cell arteritis (Journal article)
Oparaji, B. U., Clearkin, L., Ferson, S., De Angelis, M., Ferrer-Fernandez, M., Calleja, D., . . . Derrer-Merk, E. (2020). Comment on: British Society for Rheumatology guideline on diagnosis and treatment of giant cell arteritis. RHEUMATOLOGY, 59(12), E159. doi:10.1093/rheumatology/keaa265DOI: 10.1093/rheumatology/keaa265
Is "No test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of Covid-19 (Journal article)
Gray, N., Calleja, D., Wimbush, A., Miralles-Dolz, E., Gray, A., De Angelis, M., . . . Ferson, S. (2020). Is "No test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of Covid-19. PLoS One. doi:10.1371/journal.pone.0240775DOI: 10.1371/journal.pone.0240775
Gray, N., Calleja, D., Wimbush, A., Miralles-Dolz, E., Gray, A., De-Angelis, M., . . . Ferson, S. (2020). Is “no test is better than a bad test”? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19. doi:10.1101/2020.04.16.20067884DOI: 10.1101/2020.04.16.20067884
2018
Uncertainty Quantification Methods for Neural Networks Pattern Recognition (Conference Paper)
Tolo, S., Santhosh, T. V., Vinod, G., Oparaji, U., & Patelli, E. (2017). Uncertainty Quantification Methods for Neural Networks Pattern Recognition. In 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI). Retrieved from https://www.webofscience.com/
2017
Oparaji, U., Sheu, R. -J., Bankhead, M., Austin, J., & Patelli, E. (2017). Robust artificial neural network for reliability and sensitivity analyses of complex non-linear systems. NEURAL NETWORKS, 96, 80-90. doi:10.1016/j.neunet.2017.09.003DOI: 10.1016/j.neunet.2017.09.003
Oparaji, B. (2017, November 30). Robust Surrogate Models for Uncertainty Quantification and Nuclear Engineering Applications.
ROBUST ARTIFICIAL NEURAL NETWORK FOR RELIABILITY ANALYSIS (Conference Paper)
Oparaji, U., Sheu, R. -J., & Patelli, E. (2017). ROBUST ARTIFICIAL NEURAL NETWORK FOR RELIABILITY ANALYSIS. In Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120217.5400.17104DOI: 10.7712/120217.5400.17104
2016
Oparaji, U., Sheu, R. J., Bankhead, M., Austin, J., & Patelli, E. (2016). Artificial Neural Network Uncertainty Quantification for the Sensitivity Analysis of the SIXEP Model. In 13th International Conference on Probabilistic Safety Assessment and Management (PSAM 13). South Korea.