18 Aug Presentation(Big emphasis on Laws and Policy)
Order Instructions
OUTLINE
1. Consider starting with the title of your presentation and then start with a story to capture the audience’s attention.
2. Introduce your working research question and three key points you will explore to answer your question.
3. Define AI, machine learning, deep neural networks, and big data.
4. Discuss the importance of big data, the current problems, and how it’s currently used as it relates to your working research question. (This is a great opportunity for drawing on the board.)
5. Discuss how AI, ML, and neural networks are a) more efficient than our current process and b) in light of the healthcare provider shortage in developed and in developing countries; and c) how they can be used to improve the utilization of big data, healthcare costs, diagnostic wait times and resources, and improve satisfaction for healthcare professionals and patients.
6. Key point 1
7. Key point 2
8. Key point 3
9. Repeat research question and Summarize key topics you want your audience to remember.
10. Barriers, challenges, ethical concerns, and limitations.
11. Law and policy: a) current healthcare, technology and political regulations and legislation, b) arguments from supporters and opponents regarding pending proposals, c) policy opportunities locally and nationally, and d) costs and funding resources.
12. The quality of the current research.
13. Recommendations for future research.
14. Conclusion
CURRENT Topic:
How can deep neural networks in interoperability in HealthIT be used to address the Political Determinants of Health?
Political Determinants are:
Voting, Government, Policy etc. https://satcherinstitute.org/priorities/political-determinants-of-health/
https://www.healthit.gov/topic/interoperability
POTENTIAL RESEARCH TOPICS
In considering your research question, instead of talking about PDOH, here are some other ideas: regulatory/policy opportunities, the steps for clinical adoption, the globalization of machine learning, improving preventative care (access, quality, and costs), diversity of treatment algorithms and cultural sensitivity, or how machine learning can be used to improve gaps in care generally or for a specific population or specific health problem.
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VIDEOS
Bringing AI and machine learning innovations to healthcare (Google) https://youtu.be/JzB7yS9t1YE
Better medicine through machine learning (TEDx)
AI in healthcare: opportunities and challenges (TEDx) great use of simple graphics
