Tag Archives: online education

US Public Health Alphabet Soup Explained: What is the FDA?

The food and drug administration in each country serves as an agency to regulate medications.

Can you name categories other than “food” and “drugs” that are regulated by the FDA in the US? Read this blog post to learn what they are, and what the FDA does in the US.

Need an Online Curriculum in Data Science or Public Health that is Engaging? Here are my Freebies and Hacks!

This blog post talks about how I use deeper learning principles when I develop online curricula for public health and data science.

Need online curriculum in data science or public health that keeps the learners engaged? I share a links to free resources as well as my hacks to interest high!

Dumbbell Plot for Comparison of Rated Items: Which is Rated More Highly – Harvard or the U of MN?

This is an example of a dumbbell plot from the ggalt package in R that you can also use in RStudio

Want to compare multiple rankings on two competing items – like hotels, restaurants, or colleges? I show you an example of using a dumbbell plot for comparison in R with the ggalt package for this exact use-case!

US Public Health Alphabet Soup Explained: What is the BPHC?

The Bureau of Primary Healthcare is a United States federal agency that ensures safety net services to poor individuals

The United States (US) Bureau of Primary Healthcare (BPHC) is the federal agency that funds our safety net infrastructure serving patients who can’t get on Medicare or Medicaid. I explain how all that works, and the relationship of BPHC to the rest of the public health infrastructure.

US Public Health Alphabet Soup Explained: What is the APHA?

The American Public Health Association is the professional society for the occupation of public health rather than healthcare.

Curious about the American Public Health Association (APHA) – what it does, and where it fits into the bigger picture of public health organizations? I delve into these topics, and explain how you can get involved.

“Bad Blood” Highlights the Issues with No Administrative Barrier between Research and Clinical Data: Part 5 of 5

Clinical data and research data are governed by different regulations. Therefore, you cannot mix them together, but you can transfer them around from project to project.

Read my last post in a series on data-related misconduct at startup Theranos outlined in the book, “Bad Blood”, where I discuss their lack of administrative barrier between research and clinical data.

The Stages of the PDSA Model: What do they Really Mean? Part 2 of 5

Implementing the Plan Do Study Act model is very cost- and labor-intensive but it is possible to get a return on investment

What are the stages of the PDSA model, and how do they relate to the functions of a QA/QI department in healthcare? The answers are not straightforward. I examine these issues in this blog post.

“Bad Blood” Reveals Theranos was Guilty of Bad Business and Bad Data Science: Part 1 of 5

Businesses that are chaotic and poorly run do not steward their data properly, and it is inaccurate.

This is my first blog post in a series of five where I talk about data-related misconduct outlined in the book “Bad Blood”, and provide guidance on how to prevent it.

This Course in Explainable AI will Get you Ready for the Future!

What do the data say when a machine learning algorithm is applied, and which features are important?

We experience artificial intelligence all the time on the internet in terms of friend suggestions on social media, internet ads that reflect what we have been searching for, and “smart” recommendations from online stores. But the reality is that even the people who build those formulas cannot usually explain why you were shown a certain […]

Two Takeaways from Danny Ma’s Machine Learning Panel: Understanding the Problem, and Understanding your Data

Roller coaster like an ETL pipeline that does automation

This lively panel discussed many topics around designing and implementing machine learning pipelines. Two main issues were identified. The first is that you really have to take some time to do exploratory research and define the problem. The second is that you need to also understand the business rules and context behind the data.

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