Text and arrows in dataviz, if used wisely, can help your audience understand something very abstract, like a data pipeline. Read my blog post for tips in choosing images for your data visualizations!
Tag Archives: algorithms
16
Mar
Mar
Wondering what we mean by the National Institutes of Health (NIH)? In my blog post, I explain the NIH’s role in appropriating funding for research, and demystify its role in implementing federal priorities.
16
Feb
Feb
Querying the GHDx database is challenging because of its difficult user interface, but mastering it will allow you to access country-level health data for comparisons! See my demonstration!
03
Aug
Aug
You might wonder what CMS – the Centers for Medicare and Medicaid Services – actually does. This blog post provides an overview of CMS’s role and activity in the US healthcare system.
30
Jul
Jul
Getting data for meta-analysis together can be challenging, so I walk you through the simple steps I take, starting with the scientific literature, and ending with a gorgeous and evidence-based Forrest plot!
23
Jul
Jul
Want to know what AHRQ stands for, what it does, and how all that relates to US public health? AHRQ is a main player in public health – even though it is technically supposed to be focused on healthcare.
Quality Assurance/Quality Improvement (QA/QI)
“Bad Blood” is a Lesson in How Bad Leadership Leads to Bad Data: Part 4 of 5
05
Jul
Jul
As a data science leader, what should you put in place so your organization doesn’t end up a data mess like startup Theranos? This blog posts provides guidance.
Quality Assurance/Quality Improvement (QA/QI)
“Bad Blood” Demonstrates how a Lack of Product Description Leads to Data Science Misconduct: Part 2 of 5
25
Jun
Jun
This blog post talks about how lack of product description led to data-related misconduct at Theranos, because they could never nail down exactly what they were trying to do.
15
Dec
Dec
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 […]
Career Development
Two Takeaways from Danny Ma’s Machine Learning Panel: Understanding the Problem, and Understanding your Data
04
Dec
Dec
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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