Gagniuc/Diabetes-prediction-1.0
Diabetes prediction V1.0 uses the Markov Chains method. First, this VB6 application converts a sequence of numbers into states. The states are arranged in a transition matrix and the transition probabilities are calculated for each element. Next, the transition matrix is further used for a prediction in a Markov chain.
This application helps healthcare practitioners, particularly those involved in diabetes monitoring, analyze patient glycemic data. It takes a sequence of daily blood glucose readings and converts them into a sequence of 'states,' then predicts future glycemic trends based on these patterns. The output helps understand the likelihood of a patient moving between different glycemic states.
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Use this if you are monitoring individuals with a family predisposition to diabetes and want to predict short-term glycemic changes based on daily blood sugar levels.
Not ideal if you need to diagnose diabetes, model complex biological systems, or require long-term predictive analytics beyond immediate glycemic trends.
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Language
Visual Basic 6.0
License
MIT
Category
Last pushed
Nov 18, 2022
Commits (30d)
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