Disease Prediction with a Maximum Entropy Method
Machine Learning
2021-02-05 v1 Probability
Abstract
In this paper, we propose a maximum entropy method for predicting disease risks. It is based on a patient's medical history with diseases coded in ICD-10 which can be used in various cases. The complete algorithm with strict mathematical derivation is given. We also present experimental results on a medical dataset, demonstrating that our method performs well in predicting future disease risks and achieves an accuracy rate twice that of the traditional method. We also perform a comorbidity analysis to reveal the intrinsic relation of diseases.
Keywords
Cite
@article{arxiv.2102.02668,
title = {Disease Prediction with a Maximum Entropy Method},
author = {Michael Shub and Qing Xu and Xiaohua and Xuan},
journal= {arXiv preprint arXiv:2102.02668},
year = {2021}
}
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15 pages