Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model

Studying drug relationships can provide deeper information for the construction and maintenance of biomedical databases and provide more important references for disease treatment and drug development. The research model has expanded from the previous focus on a certain drug to the systematic analys...

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Main Authors: Hui Teng, Yukun Ma, Di Teng
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/8839563
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author Hui Teng
Yukun Ma
Di Teng
author_facet Hui Teng
Yukun Ma
Di Teng
author_sort Hui Teng
collection DOAJ
description Studying drug relationships can provide deeper information for the construction and maintenance of biomedical databases and provide more important references for disease treatment and drug development. The research model has expanded from the previous focus on a certain drug to the systematic analysis of the pharmaceutical network formed between drugs. Network model is suitable for the study of the nonlinear relationship of the pharmaceutical relationship by modeling the data learning. Association rule mining is used to find the potential correlations between the various sets of massive data. Therefore, based on the network model, this research proposed an algorithm for drug interaction under improved association rules, which achieved accurate analysis and decision-making of drug relationship. Meanwhile, this research applied the established association rule algorithm to discuss the relationship between Chinese medicine and mental illness medicine and conducted the algorithm research and simulation analysis of the association relationship. The results showed the association rule algorithm based on the network model constructed was better than other association algorithms. It had reliability and superiority in decision-making in improving the drug-drug relationship. It also promoted the rational use of medicines and played a guiding role in pharmaceutical research. This provides scientific research personnel with research basis and research ideas for disease-related diagnosis.
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institution Kabale University
issn 1076-2787
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language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-d443c986244e45d1b4e729ff0d1cbfa82025-02-03T06:47:00ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/88395638839563Algorithm and Simulation of Association Rules of Drug Relationship Based on Network ModelHui Teng0Yukun Ma1Di Teng2Basic Medical Science College, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, ChinaInstitute of Medical Sciences College, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, ChinaBasic Medical Science College, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, ChinaStudying drug relationships can provide deeper information for the construction and maintenance of biomedical databases and provide more important references for disease treatment and drug development. The research model has expanded from the previous focus on a certain drug to the systematic analysis of the pharmaceutical network formed between drugs. Network model is suitable for the study of the nonlinear relationship of the pharmaceutical relationship by modeling the data learning. Association rule mining is used to find the potential correlations between the various sets of massive data. Therefore, based on the network model, this research proposed an algorithm for drug interaction under improved association rules, which achieved accurate analysis and decision-making of drug relationship. Meanwhile, this research applied the established association rule algorithm to discuss the relationship between Chinese medicine and mental illness medicine and conducted the algorithm research and simulation analysis of the association relationship. The results showed the association rule algorithm based on the network model constructed was better than other association algorithms. It had reliability and superiority in decision-making in improving the drug-drug relationship. It also promoted the rational use of medicines and played a guiding role in pharmaceutical research. This provides scientific research personnel with research basis and research ideas for disease-related diagnosis.http://dx.doi.org/10.1155/2020/8839563
spellingShingle Hui Teng
Yukun Ma
Di Teng
Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model
Complexity
title Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model
title_full Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model
title_fullStr Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model
title_full_unstemmed Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model
title_short Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model
title_sort algorithm and simulation of association rules of drug relationship based on network model
url http://dx.doi.org/10.1155/2020/8839563
work_keys_str_mv AT huiteng algorithmandsimulationofassociationrulesofdrugrelationshipbasedonnetworkmodel
AT yukunma algorithmandsimulationofassociationrulesofdrugrelationshipbasedonnetworkmodel
AT diteng algorithmandsimulationofassociationrulesofdrugrelationshipbasedonnetworkmodel