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Predicting Antimicrobial Resistance Trends Combining Standard Linear Algebra with Machine Learning Algorithms
Castiglione, F., Daugulis, P., Mancini, E., Oldenkamp, R., Schultsz, C. & Vagale, V., Jan 2024, In: Baltic Journal of Modern Computing. 12, 1, p. 30-49 20 p.Research output: Contribution to journal › Article* › Academic › peer-review
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An agent-based multi-level model to study the spread of antimicrobial-resistant gonorrhoea
Stolfi, P., Vergni, D., Oldenkamp, R., Schultsz, C., Mancini, E. & Castiglione, F., 2022, Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022: [Proceedings]. Adjeroh, D., Long, Q., Shi, X., Guo, F., Hu, X., Aluru, S., Narasimhan, G., Wang, J., Kang, M., Mondal, A. M. & Liu, J. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 803-808 6 p. (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution* › Academic › peer-review
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Filling the gaps in the global prevalence map of clinical antimicrobial resistance
Oldenkamp, R., Schultsz, C., Mancini, E. & Cappuccio, A., 5 Jan 2021, In: Proceedings of the National Academy of Sciences of the United States of America. 118, 1, e2013515118.Research output: Contribution to journal › Article* › Academic › peer-review
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