I would start by getting a lot of the parameters you need in a database such as SQLite (comes with python).
So for example, you would have a disease with known symptoms. You could structure your tables with diseases symptoms So, say the disease is a cold in the table you will have a row for cold and columns identifying each symptom (by unique IDs). In your symptom table you would have a row for each symptom and a column for its parameters and probabilities and such. For example, gender exclusive, age exclusive, geographic exclusive, workplace, etc. >From there you can build your select statements on the fly using python's string formating. That's how i would do it anyway. I'm sure there are other ways as well. On Mon, Jun 13, 2011 at 10:22 AM, Fred G <bayespoker...@gmail.com> wrote: > Hello-- > > I'm a pre-med student interested in decision-making as applied to medical > decisions. I am trying to build a medical decision-making algorithm and am > pretty stuck on a few things. > > I've built a file that contains a list of many diseases and their > associated symptoms. For example, here are the column headers and two > sample rows (the "|" = "or"): > Disease Symptoms > Cold > sore_throat|runny_nose|congestion|cough|aches|slight_fever > Flu > sore_throat|fever|headache|muscle_aches|soreness|congestion|cough|returning_fever > > My questions are the following: > a) How's the best way to make it so I can have a user type in a list of > symptoms and then have the computer tell the user the possible diseases that > share those symptoms? In other words, on a high-level I have a pretty good > idea of what I want my algorithm to do-- but I need help implementing the > basic version first. I'd like to do the following: > >>>Please enter a list of symptoms > >>>[user_input] > >>>Possible diseases include: x, y, z > > b)Once I get that working, could anyone point me to good code already > written in Python such that I could have a model (for syntax and overall > structure) for figuring out how to make the computer evaluate more factors > such as: patient age, patient history, and even downloading archival data > for patients in the same demographic group? > > Thanks! > > > > _______________________________________________ > Tutor maillist - Tutor@python.org > To unsubscribe or change subscription options: > http://mail.python.org/mailman/listinfo/tutor > >
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