Using Data Science to Help Women Make Contraceptive Choices

Didn’t read entirely but it looks like collaborative filtering based on preferences. That’s fine. When I saw the headline I thought it might be a personalized medicine model that predicted side effects of different hormonal treatments using whatever omics. That would be a really impactful area to do some data science. There’s probably a lot of low hanging fruit, and there’s really no good resources as far as I can tell to help women choose which contraceptives will negatively impact them the least.

Looks like a fun little data science project but I don't see any data here that would be useful to determine similarity among women and thus who would benefit from which type of BC. The closest thing I see is age. I think you'll need a better data set if you want to make something that's more useful. That said it's a good idea in general - someone should get on that.

This is essentially a "job market paper" for a data science bootcamp for recent PhDs.

The contents are nothing groundbreaking but just an exploration of how different models and data sources can be used to predict something. Insofar as the purpose is to demonstrate the author could do the same sort of analysis about questions like will customers buy your product based on unstructured reviews posted on amazon, I think its successful.

The only problematic aspect seems to be the notion that you can "recommend" a form of birth control based on modeling preferences. This is definitely a Jurassic Park type of article, interesting because it's so clear that data science built on self reported information on reddit is a bad way to actually recommend options when there are much better method available (e.g. professionals).

Side Question: What would the developed world be like if contraception didn't exist? how would this reflect in our culture/media?