Contributions to COVID-19 pandemic data analysis

• Autores: Goizalde Badiola Zabala
• Directores de la Tesis: Manuel Graña Romay (codir. tes.) , José Manuel López Guede (codir. tes.)
• Lectura: En la Universidad del País Vasco - Euskal Herriko Unibertsitatea ( España ) en 2024
• Idioma: inglés
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• Resumen

  • This thesis deals with various aspects of data analysis during the COVID-19 pandemic. This thesis provides important insights into the epidemiological trends and clinical decision support during the COVID-19 pandemic through data analysis and Machine Learning. Initially, the study examines clinical deci- sion support systems used during pandemics. It then provides a detailed analysis of a COVID-19 patient from a local dataset, including data normalization and class balancing to improve prediction accuracy. Additionally, the Thesis considers several aspects of COVID-19 epidemiology that raise questions about the efficacy of the interventions in several countries.