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A Bayesian-based prediction model for personalized medical health care
Conference proceeding

A Bayesian-based prediction model for personalized medical health care

Jiashu Zhao, Jimmy Xiangji Huang, Xiaohua Hu, J Kurian and W Melek
2012 IEEE International Conference on Bioinformatics and Biomedicine, pp 1-4
Oct 2012
DOI: https://doi.org/10.1109/BIBM.2012.6392623

Abstract

Bayesian Learning Bayesian methods BFLT Correlation Laboratories Laboratory Test Prediction Medical diagnostic imaging Medical Health Care Medical services Predictive models Smoothing Technique
In this paper, we present a Bayesian-based Personalized Laboratory Tests prediction (BPLT) model to solve a real world medical problem: how to recommend laboratory tests to a group of patients? Given a patient who has conducted several laboratory tests, BPLT model recommends further laboratory tests that are the most related to this patient. We regard this laboratory test prediction problem as a special classification problem, where a new laboratory test belongs to either a "taken" or "not-taken" class. Our goal is to find the laboratory tests with high probability of "taken" and low probability of "not taken". Based on Bayesian method, the BPLT model builds a weighting function to investigate the correlations among laboratory tests and generate the rank of laboratory tests. In order to evaluate the proposed BPLT model, we further propose a novel evaluation metric to subjectively measure the accuracy of BPLT model. Experimental results show that BPLT model achieves good performance on the real data sets and provides a good solution to our real world application.

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3 citations in Scopus

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