Public Health Informatics

Good afternoon!

Imagine having the power to exponentially accelerate your diagnostic capabilities, automate routine tasks, and seamlessly collaborate with other labs through cutting-edge AI and machine learning integrated informatics systems. How might embracing these technologies streamline your current workflows and empower your lab's respond to emerging public health challenges with speed and precision?

From an informatics perspective, these technologies hold the potential to revolutionize data management, analysis, and decision-making processes within public health systems. I've included an infographic from Technology Networks that shares some interesting insights from a recent Pistoia Alliance survey completed in Sept. of 2023. The study identified the overwhelming investment into AI and MI, with 60% of companies surveyed stating it was one of their top three funding priorities. Additionally, the survey identified many of the barriers standing adoption of AI and other lab digitization.

I'm looking for experiences, comments, and questions from the community in these areas for a possible forum discussion. Please share your story or pose a question so we may dig deeper and provide answers.

Thanks!

Attachment(s)

TN_Infographic_AI_LOTF_2023.pdf   1.21 MB 1 version

• Discussed the integration of AI into public health lab operations, focusing on generative AI for creating new content.
• Emphasized the significance of prompt design in utilizing AI effectively, highlighting its use in generating policy documents and auditing existing policies.
• Pointed out the potential of AI to streamline lab workflows and enhance efficiency in public health settings.

• Provided an overview of AI and machine learning, demystifying their applications in biodefense and public health.
• Stressed the importance of understanding AI capabilities and limitations, advocating for the use of AI as a tool to augment human expertise.
• Highlighted practical examples of AI applications, encouraging critical thinking and the development of AI literacy among public health professionals.

• Introduction and Purpose of the Meeting:
• The meeting opens with an overview of the agenda and the importance of AI in enhancing public health laboratory operations.
• True Merrill's Presentation:
• AI and Machine Learning Basics: Merrill starts by demystifying AI and machine learning, clarifying common misconceptions and introducing their fundamental principles.
• Applications in Public Health: He discusses AI's potential in biodefense and public health, providing examples of current applications and future possibilities.
• Challenges and Opportunities: Merrill highlights the importance of understanding AI's capabilities and limitations, emphasizing the need for critical thinking and human oversight in AI implementation.
• David Silva's Presentation:
• Generative AI in Public Health Labs: Silva introduces generative AI and its capacity to create new content, focusing on its role in policy document creation and policy auditing.
• The Significance of Prompt Design: He stresses the importance of designing effective prompts for AI interactions, sharing tips and strategies for public health professionals.
• Practical Implementations and Case Studies: Silva shares examples of how generative AI is being used in Dallas County Public Health Lab, underscoring the technology's impact on operational efficiency.
• Discussion and Q&A:
• Participants engage in a discussion with the speakers, asking questions about AI integration challenges, data privacy, and the future of AI in public health.
• Both speakers emphasize the importance of collaboration between AI experts and public health professionals to navigate the evolving landscape of AI technologies.
• Closing Remarks:
• The forum concludes with closing remarks from the organizers, summarizing key takeaways and encouraging attendees to explore AI opportunities within their organizations.

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