ePublished: 29 Jun 2016
EndNote EndNote

(Enw Format - Win & Mac)

BibTeX BibTeX

(Bib Format - Win & Mac)

Bookends Bookends

(Ris Format - Mac only)

EasyBib EasyBib

(Ris Format - Win & Mac)

Medlars Medlars

(Txt Format - Win & Mac)

Mendeley Web Mendeley Web
Mendeley Mendeley

(Ris Format - Win & Mac)

Papers Papers

(Ris Format - Win & Mac)

ProCite ProCite

(Ris Format - Win & Mac)

Reference Manager Reference Manager

(Ris Format - Win only)

Refworks Refworks

(Refworks Format - Win & Mac)

Zotero Zotero

(Ris Format - Firefox Plugin)

Int J Basic Sci Med. 2016;1: 13-17.
doi: 10.15171/ijbsm.2016.04
  Abstract View: 2261
  PDF Download: 2022
  Full Text View: 2337

Original article

Dynamic Recommendation: Disease Prediction and Prevention Using Recommender System

Mahdi Nasiri 1*, Behrouz Minaei 1, Amir Kiani 2

1 Computer Engineering Department, Iran University of Science and Technology (IUST), Tehran, Iran
2 Department of Mathematics and Computer Science, Amir Kabir University of Technology, Tehran, Iran
*Corresponding Author: *Correspondence to: Mahdi Nasiri;, Email: nasiri_m@comp.iust.ac.ir


Background: In today’s world, chronic diseases are predominant health problems and cause heavy burden on society; therefore early diagnosis and even prediction of the disease is a way to reduce this burden. In this project, we tried to use recommender system to predict which other diseases a chronic patient is susceptible for.

Methods: In this study, through a dynamic recommender system, we evaluated patients’ treatment destiny during the time.

Results: It was shown that our method increased accuracy and reduced error compared with other recommendation methods in disease prediction.

Conclusion: Compared to current usual methods, in our method we used previous patients’ characteristics as one of the factorization variables to predict destiny of future patients. Furthermore, using this method, we can predict which complication or disease the patient would suffer from first in future. Therefore, we can manage policies toward disease burden reduction by implementing prevention programs.

Keywords: Recommender system, Disease prediction, Collaborative filtering, Data mining, Treatment

Please cite this article as follows: Nasiri M, Minaei B, Amir Kiani A. Dynamic recommendation: disease prediction and prevention using recommender system. Int J Basic Sci Med. 2016;1(1):13-17. doi:10.15171/ijbms.2016.04.
First Name
Last Name
Email Address
Security code

Abstract View: 2262

Your browser does not support the canvas element.

PDF Download: 2022

Your browser does not support the canvas element.

Full Text View: 2337

Your browser does not support the canvas element.