In article <[EMAIL PROTECTED]>,
Jeff Goslin <[EMAIL PROTECTED]> wrote:
>Hi Steve, thanks for your reply.
>"Simon, Steve, PhD" wrote:
>> Many of us on the list are skeptical about artificial intelligence methods.
>> They have proven useful for some applications, but they are often marketed
>> as if they can substitute for consultation with a professional statistician.
>Have no fear, my application would by no means hand you or your brethren a pink
>slip. ;)
>> Putting aside that skepticism, have you thought about how you are going to
>> measure how successful your neural net is at mimicking a human pancreas? In
>> particular, you do not seem to have data on insulin production, so how will
>> you know that the neural net pancreas produces insulin at a rate comparable
>> to the human pancreas?
>Among the data that I am using are basal and bolus amounts of insulin injected
>by the patient(roughly translated, small amounts throughout the day(basal) and a
>large amount during meals(bolus)). This information will be used as a baseline
>to train the neural net or genetic algorithm on how much insulin produces the
>desired result. The data that I need to have "tweaked" or "interpolated", is
>the blood sugar readings themselves. The standard practice of an insulin
>dependant diabetic is to check blood sugars at various times during the day, and
>then apply booster shots of insulin as needed. This is, of course, NOT the way
>the human pancreas works. It provides a steady stream of insulin as necessary
>as the blood glucose levels in the body rise and fall throughout the day. By
>reading a blood sugar on a minute by minute basis and then producing smaller
>dosages of insulin over a prolonged period, the pancreas operation may be
>effectively simulated.
I suggest you learn a little more. The "steady stream"
injects insulin into fatty tissue, from which it seeps at a
more or less constant rate into the blood stream. A
posting by an endocrinologist stated that the half-life of
insulin in the blood stream is nine minutes, so this type
of delivery is needed. There have been some experiments
done with direct intravenous injection of insulin.
>Since I only have data for patients where they are checking their blood sugars
>at most 10 times a day, I need to get a minute by minute best guess as to the
>condition of the blood sugar, based on the actual data I have.
I would be surprised if there have not been such studies
already. You seem to be trying to reinvent the wheel.
>The success of the neural net will be measured on how effectively the program
>remains within the 80-120 blood sugar reading deemed "normal" for a Type I
>diabetic. Too much insulin, the blood sugar readings dip into dangerously low
>levels, a bad thing. Too little insulin, the blood sugar readings skyrocket,
>also, a bad thing. By comparing the output of the AI to actual readings, I will
>be able to guage how effectively the AI is at determining how much insulin to
>give, based on previous readings.
This is not achieved for "normal" people. I doubt that
it can be done, unless very carefully designed meals are
eaten, with only low glycemic index carbohydrates, and
not even that. Also, the liver and kidneys convert their
stores of glycogen to blood glucose on the appropriate
triggers.
>Suffice it to say, the amounts of insulin delivered do not need tweaking. Only
>the blood sugars.
You do not know when the insulin is delivered to the
blood stream. The fastest insulin delivered to fatty
tissue takes hours to completely enter the blood stream.
This is another variable, and it is variable. The only
way you could know the amount of insulin is to use
more complicated tests for it; these are usually not
done, except by medical researchers.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
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