Utilising machine learning in the battle against Covid-19: a focus on healthcare resource allocation
Veneziani, Emanuele (A.A. 2022/2023) Utilising machine learning in the battle against Covid-19: a focus on healthcare resource allocation. Tesi di Laurea in Artificial intelligence and machine learning, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 58. [Bachelor's Degree Thesis]
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Abstract/Index
Literature review. The Covid-19 pandemic and its impact on healthcare systems. Challenges in allocating resources in hospitals during pandemics. The role of AI and machine learning, in healthcare amidst the Covid-19 pandemic. Theoretical background. Introduction to machine learning. Relevant machine learning models for resource allocation: adjutotium and COXREG. Ethical and legal considerations in AI and machine learning. Analysis. Potential benefits of machine learning in allocating resources during pandemics. Limitations and challenges in implementing machine learning for resource allocation in pandemics. The future of machine learning, in allocating resources during pandemics.
References
Bibliografia: pp. 55-57.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Artificial intelligence and machine learning |
| Thesis Supervisor: | Italiano, Giuseppe Francesco |
| Academic Year: | 2022/2023 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 08 Mar 2024 16:41 |
| Last Modified: | 08 Mar 2024 16:41 |
| URI: | https://tesi.luiss.it/id/eprint/38159 |
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