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Published on: May 1, 2021
Transforming Public Health Practice with Artificial Intelligence: A Framework-Driven Approach
Obinna O Oleribe1,2, Florida Uzoaru3, Adati Tarfa4
1Department of Health Sciences, School of Public Health and Health Sciences, California State University, Dominguez Hills, 1000 E Victoria Street, Carson, CA 90747, USA.
Artificial intelligence (AI) offers transformative potential for public health, enhancing interventions and crisis response. Adopting a Public Health AI Framework ensures equitable development and deployment of AI for improved health outcomes.
Area of Science:
- Public Health
- Artificial Intelligence
- Health Informatics
Background:
- Artificial intelligence (AI) is revolutionizing healthcare, impacting public health functions like disease surveillance, health promotion, and policy development.
- While AI is integrated into many public health operations, its application in leadership and management is still developing.
- The study addresses the evolving role of AI in public health practice and leadership.
Purpose of the Study:
- Propose the Public Health AI Framework for AI development in public health.
- Ensure inclusive data, appropriate policies, and strategic partnerships in AI initiatives.
- Maximize AI potential through trained human-relevant resources.
Main Methods:
- Conceptual framework development.
- Literature review on AI applications in public health.
- Analysis of AI's role in public health leadership and management.
Main Results:
- AI can personalize interventions, democratize data access, and improve crisis response.
- AI has the potential to advance health equity and strengthen environmental health resilience.
- Effective AI integration requires proactive leadership and collaboration between public health professionals and AI specialists.
Conclusions:
- AI offers significant opportunities to reshape public health practices and outcomes.
- A deliberate leadership vision is crucial for co-creating and deploying AI tools in public health.
- Public health professionals should actively co-innovate to ensure ethical and equitable AI evolution.
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