it crashed :(
Mosquitos probing through a net: https://i.imgur.com/Adu9PV7.gifv
COOL gif but also GROSS
*goes back to parameterizing her model*
ftr this is not a rag on my boss it's just amusing to me that someone leaves it until the last day of the semester in a modeling class before realizing they don't get that.
I suspect before I showed up, new lab had lab meetings with seriously detailed powerpoints.
Since I showed up, we've been small enough that stopped.
With several new grad students having accepted offers here, I'm worried that will start again.
BAN POWERPOINTS (they are not effective ways to convey information in a collaborative framework).
anyway, ML is a hot topic in biology right now. Some cool regression tree/random forest projects are happening.
BUT in most public health cases we have
1) small data
2) human decision makers who make decisions without clearly stated objectives
so uh. ML isn't necessarily gonna get us anything.
More recently, we simulated a metapopulation with a gradient of coverage and two primary regions - one chunk of locales where disease had been eliminated and another where it was on the route to elimination.
We tried to classify those regions using a neural network.
That also failed (although I think a friend's still working on it).
At one point we tried to use reinforcement learning to discover a heuristic for when you should switch from your "achieving" strategy to your "maintaining" strategy along a gradient of vaccination coverage, using some immune summary statistics as state space.
In the end we got out some facts about our model for disease/immunity and no useful heuristic.
It turns out machine learning is not great for discovering heuristics.
I am a queer womanb broadly interested in:
infectious disease dynamics
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