Document Type

Student Paper

Publication Date

2021

Research Program

TREB

First Advisor

Dr. Janne Flory

Abstract

As the world emerges from the COVID-19 pandemic, it is critical to reflect on the lessons learned and prepare for potential future health crises. While data analytics and artificial intelligence (AI) played a pivotal role in managing the pandemic, there is much room for improvement and further use. This study examines the current state of data science tools employed during COVID-19, evaluating their advantages, limitations, and challenges in their broader implementation. We also review literature on future directions for AI in healthcare. Our findings highlight significant challenges, including difficulties in accessing usable data and common distrust of AI models for pandemic forecasting and diagnostics. There is also a major concern regarding data security, especially with regard to the vast personal health information necessary for data analysis and AI modeling. However, we also identify promising diagnostic models, particularly those based on chest X-rays, blood tests, and facial imaging, which demonstrate high accuracy and speed—potentially offering alternatives to traditional testing methods like PCR tests. As data analytics continues to evolve and gain acceptance, it has the potential to significantly enhance global preparedness and colaboration for future pandemics and other large-scale health crises.

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