An Ontology Based System for Storing the Research Results on Medical Diagnostics

This paper proposes an ontology based system for storing information on medical diagnostics. The proposed system is focused on a specific way of storing the medical content – it allows the user not only to store standard information in a medical domain, but gives an opportunity to store the ongoing research. The main contribution of this system is its extensibility to contain all types of medical information and its capability to provide the needed research material at hand, including the quickly way of finding and evaluating the controversial current results. This makes it possible for researchers to work together in team and remotely. The system has been tested on real experimental data we obtained in the diagnosis of lung cancer based on gene expression. The experiments have shown that the proposed system tends to cover the needs of users.

[1]  Sofia Cramerotti,et al.  An Ontology-based System for Building Individualized Education Plans for Students with Special Educational Needs , 2016 .

[2]  Radziah Mohamad,et al.  Medical Ontology in the Dynamic Healthcare Environment , 2012, ANT/MobiWIS.

[3]  Maxim D Podolsky,et al.  Evaluation of Machine Learning Algorithm Utilization for Lung Cancer Classification Based on Gene Expression Levels. , 2016, Asian Pacific journal of cancer prevention : APJCP.

[4]  Mohammed Elmogy,et al.  An encoding methodology for medical knowledge using SNOMED CT ontology , 2016, J. King Saud Univ. Comput. Inf. Sci..

[5]  Natalia Gusarova,et al.  An ontology approach to storing educational information , 2016, 2016 International FRUCT Conference on Intelligence, Social Media and Web (ISMW FRUCT).

[6]  Jonghun Park,et al.  FlowWiki: A wiki based platform for ad hoc collaborative workflows , 2011, Knowl. Based Syst..

[7]  Zoran Budimac,et al.  An overview of ontologies and data resources in medical domains , 2014, Expert Syst. Appl..

[8]  Jaya Sil,et al.  Gene selection for designing optimal fuzzy rule base classifier by estimating missing value , 2017, Appl. Soft Comput..

[9]  Jason J. Jung Computational reputation model based on selecting consensus choices: An empirical study on semantic wiki platform , 2012, Expert Syst. Appl..

[10]  Natalia Gusarova,et al.  Analysis of the Classification Methods of Cancer Types by Computer Tomography Images , 2016 .

[11]  U. Stephani,et al.  Gene expression analysis in untreated absence epilepsy demonstrates an inconsistent pattern , 2017, Epilepsy Research.

[12]  Amy J. C. Trappey,et al.  Using Patent Ontology Engineering for Intellectual Property Defense Support System , 2012, ISPE CE.