Health and Technology

, Volume 9, Issue 1, pp 37–44 | Cite as

Prediction of disease based on prescription using data mining methods

  • Shiva Kazempour Dehkordi
  • Hedieh SajediEmail author
Original Paper


The volume of data being gathered every day is large and health care societies correspondingly generate a large volume of information daily. Although health care industry is rich in information but it requires discovering concealed relationships and patterns in data. The aim of this paper is employing data mining methods to find out knowledge in a dataset that was provided by a research center. By analyzing the drugs that were bought by each patient, our proposed method aims to predict the type of physician each patient has referred to and the type of disease he is suffering from. Our collected dataset contains details such as sex, age and the names of the drugs prescribed for each patient. For labeling the instances, a group of pharmacy students and professors has determined each patient’s disease. A number of experiments have been performed to compare the performance of different data mining techniques for predicting the diseases and the results illustrate that the proposed Stacking Model has higher accuracy compared to other data mining techniques such as k-Nearest Neighbor (kNN).


Data mining Predicting disease Stacking learning algorithm 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

12553_2018_246_MOESM1_ESM.xlsx (1.9 mb)
ESM 1 (XLSX 1976 kb)


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Copyright information

© IUPESM and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mathematics, Statistics and Computer Science, College of ScienceUniversity of TehranTehranIran

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