Year: 2025
Author: Michael Shub, Qing Xu, Xiaohua Xuan
CSIAM Transactions on Life Sciences, Vol. 1 (2025), Iss. 1 : pp. 134–152
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 International Classification of Diseases, tenth revision, 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.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/csiam-ls.SO-2024-0004a
CSIAM Transactions on Life Sciences, Vol. 1 (2025), Iss. 1 : pp. 134–152
Published online: 2025-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 19
Keywords: Disease prediction maximum entropy bioinformatics.