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Artificial Intelligence in Health AI in the battle against COVID-19

10.1. Country-specific implementations These case studies underscore the importance of careful

10.1.1. South Korea’s AI-powered response management of AI applications in pandemic response
efforts. Success depends not only on the technology itself
South Korea’s response to the COVID-19 pandemic is but also on factors such as data quality, user engagement,
a prime example of effective AI implementation. The and the ethical use of AI.
country’s swift action in developing AI-driven testing,
tracing, and treatment strategies resulted in the efficient 11. Future directions
containment of the virus. AI algorithms were employed to The COVID-19 pandemic has accelerated the integration of
analyze travel and medical data, facilitating rapid contact AI in healthcare and public health. Looking ahead, several
tracing and targeted testing. 86-88 Chatbot services such as emerging technologies and policy recommendations could
the Korean COVID-19 chatbot provided citizens with real- shape the next phase of AI in pandemic preparedness and
time information by integrating public data from the Korea response.
Centers for Disease Control and Prevention and Ministry
of Health and Welfare, thereby easing the burden on 11.1. Emerging technologies
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national health-care hotlines. Quantum computing holds the promise of processing
10.1.2. Singapore’s TraceTogether program complex datasets much faster than traditional computers.
In the context of pandemics, quantum algorithms could
Singapore launched the TraceTogether program, which revolutionize the way we model viral spread, optimize
utilized a mobile application and token-based system to supply chains for medical supplies, and discover new
facilitate digital contact tracing. The technology behind therapeutic drugs. 96
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the program assessed the proximity and duration of user
interactions to notify individuals of potential exposure Next-generation sequencing (NGS) technologies are
to the virus. While innovative, the program encountered rapidly evolving, allowing for quicker and more affordable
challenges related to user privacy and data security. 91 genomic sequencing. AI, combined with NGS, could
enable real-time tracking of pathogen evolution, helping
10.1.3. The United States’ vaccine distribution public health officials stay ahead of mutations and variants
of concern. 97
In the United States, AI played a crucial role in optimizing
vaccine distribution logistics. Recurrent neural networks Blockchain technology offers a secure and transparent
helped identify optimal locations for vaccine centers and way to manage health data. In pandemics, blockchain can
manage supply chains. However, the reliance on AI also led ensure the integrity of health records, facilitate secure data
to some disparities in vaccine allocation, highlighting the sharing for AI algorithms, and support contact tracing
need for oversight in AI implementations. 92 efforts without compromising privacy. 98
10.2. Success stories and failures 11.2. Policy recommendations
AI-driven diagnostic tools have emerged as a success story, Robust data governance frameworks are essential to ensure
with algorithms such as those developed by DeepMind that AI systems have access to high-quality, representative
capable of predicting the structure of proteins associated data while safeguarding individual privacy. Policies must
with SARS-CoV-2, the virus causing COVID-19. This be developed to address data ownership, consent, and
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breakthrough holds implications for understanding the anonymization. 99
virus’s mechanisms and developing treatments. Given the global nature of pandemics, international
Moreover, AI has proven successful in disseminating cooperation is imperative. Policy recommendations should
public health messaging via social media platforms, encourage the sharing of AI technologies and expertise
chatbots, and other digital means. These AI systems have across borders, as well as fostering collaborative efforts in
effectively tailored messages to specific demographics, research and development. 100
thereby improving public engagement and compliance To fully harness the potential of AI, investments in
with health guidelines. 94 education and workforce development are crucial. This
Conversely, some AI predictive models have failed to effort includes training healthcare professionals in AI
provide accurate forecasts for the spread of the virus. In applications and promoting AI literacy among the general
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many instances, these models were unable to account for population.
the dynamic nature of human behavior and policy changes, The future of AI in the context of pandemics is
leading to over- or under-estimation of case numbers. 95 promising, with emerging technologies offering new tools

Volume 1 Issue 2 (2024) 9 doi: 10.36922/aih.2401