Mammogram Investment for a Mammoth Impact

Predicting state populations with least squares regression & determining the relative risk of new breast cancer cases per state by incorporating external data on cancer rates in different age groups.

Comment 5

IMPORTANT

The chloropleths in the slideshow are generally not to scale, the contrast between colors was enhanced to show the difference between different values.

Slides

https://docs.google.com/presentation/d/13n6YK7mXIKajjAV9gYas-c-5jCvxulCMF7yPud_fMVs/edit?usp=sharing

What it does

Predicts the best states for FDA to invest in mammogram detection.

How we built it

Using pandas, jupyter notebook, python

Challenges we ran into

It was challenging to use pandas to manipulate data, since this is my first time doing so. To get over this, I reviewed the slides from the beginner workshop and used more general python code to manipulate data, which I was more familiar with.

Accomplishments that we're proud of

It was my first datathon project, and it was a lot of fun! I'll definitely do it next year too.

Built With

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Updates

posted an update —

The overcapacity statistic numbers in the final chloropleth (4.34m, 1.2m, etc), don't represent the number of people for something, it is just the value of the statistic. A single value of the statistic does not mean anything on its own, its significance comes from being compared with the overcapacity statistics in other states to determine whether one state will have more overcapacity than the other.

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