Abstract
Background: One of the most interesting and important topics in the field of information systems and knowledge management is the concept of eliciting rules and collecting the knowledge of human experts in various subjects to be used in expert systems. Many scientists have used decision support systems to support businesses or organizational decision-making activities, including clinical decision support systems for medical diagnosis.
Objective: In this study, a rough set based expert system is designed for the diagnosis of one type of blood cancer called multiple myeloma. In order to improve the validity of generated models, three condition attributes that define the shape of “Total protein”, “Beta2%” and “Gamma%” are added to the models to improve the decision attribute value domain.
Methods: In this study, 1100 serum protein electrophoresis tests are investigated and based on these test results, 15 condition attributes are defined. Four different rule models are obtained through extracting rules from reducts. Janson and Genetic Algorithm with "Full" and "ORR" approaches have been used to generate reducts.
Results: The GA/ORR of the information system with 87% accuracy is used as an inference engine of an expert system and a unique user interface is designed to automatically analyze test results based on these generated models. Gamma% is detected as a core attribute of the information system.
Conclusion: Based on the results of generating reducts, the Gamma% attribute is detected as a core of the information system. This means that information, which is resulted from this conditional attribute, has the greatest impact on the diagnosis of multiple myeloma. The GA/ORR model with 87% accuracy is selected as the inference engine of the expert system and finally, a unique user interface is created to help specialists diagnose multiple myeloma.
Keywords: Rough set, expert system, inference engine, multiple myeloma, artificial intelligence, computer science.
Recent Advances in Computer Science and Communications
Title:Designing an Expert System for the Diagnosis of Multiple Myeloma by Using Rough Set Theory
Volume: 14 Issue: 6
Author(s): Tooraj Karimi*, Arvin Hojati and Reza Razavi
Affiliation:
- Faculty of Management and Accounting, University of Tehran, Tehran,Iran
Keywords: Rough set, expert system, inference engine, multiple myeloma, artificial intelligence, computer science.
Abstract:
Background: One of the most interesting and important topics in the field of information systems and knowledge management is the concept of eliciting rules and collecting the knowledge of human experts in various subjects to be used in expert systems. Many scientists have used decision support systems to support businesses or organizational decision-making activities, including clinical decision support systems for medical diagnosis.
Objective: In this study, a rough set based expert system is designed for the diagnosis of one type of blood cancer called multiple myeloma. In order to improve the validity of generated models, three condition attributes that define the shape of “Total protein”, “Beta2%” and “Gamma%” are added to the models to improve the decision attribute value domain.
Methods: In this study, 1100 serum protein electrophoresis tests are investigated and based on these test results, 15 condition attributes are defined. Four different rule models are obtained through extracting rules from reducts. Janson and Genetic Algorithm with "Full" and "ORR" approaches have been used to generate reducts.
Results: The GA/ORR of the information system with 87% accuracy is used as an inference engine of an expert system and a unique user interface is designed to automatically analyze test results based on these generated models. Gamma% is detected as a core attribute of the information system.
Conclusion: Based on the results of generating reducts, the Gamma% attribute is detected as a core of the information system. This means that information, which is resulted from this conditional attribute, has the greatest impact on the diagnosis of multiple myeloma. The GA/ORR model with 87% accuracy is selected as the inference engine of the expert system and finally, a unique user interface is created to help specialists diagnose multiple myeloma.
Export Options
About this article
Cite this article as:
Karimi Tooraj *, Hojati Arvin and Razavi Reza, Designing an Expert System for the Diagnosis of Multiple Myeloma by Using Rough Set Theory, Recent Advances in Computer Science and Communications 2021; 14 (6) . https://dx.doi.org/10.2174/2666255813666191219105821
DOI https://dx.doi.org/10.2174/2666255813666191219105821 |
Print ISSN 2666-2558 |
Publisher Name Bentham Science Publisher |
Online ISSN 2666-2566 |
Call for Papers in Thematic Issues
?The New Era of Computational Intelligence: Big Data Applications in Health Care?
Analyzing healthcare data has remained a tedious task for data analysts in the current age of research due the nonlinear nature of data. With data sources multiplying and their complexity rising, the most common challenge for medical analysts today is obtaining relevant data for those that need it. The challenge ...read more
Advanced Applications of Artificial Intelligence in Manufacturing Technologies
As one of the most advanced fields of study and technology in existence today, artificial intelligence (AI) is finding more and more applications in production and daily life, especially in the industrial sector. This showcases the many applications of AI in mechanical production, including but not limited to: improving worker ...read more
Advanced integration of computer vision and AI algorithms for automated applications in vehicles
Automation is a key component of present automobile industry to enhance the innovation through artificial intelligence. Intelligent automation in the autonomous vehicles can replace humans and provide better safety movements of vehicles. Global shift towards human to automation needs high risk mitigation technologies. The vast challenges of autonomous vehicles are ...read more
Advancing Computer Vision and Multimedia Communication for Seamless Human-Machine Interaction
The rapid advancements in computer vision and multimedia communication technologies are revolutionizing the way humans interact with machines. These technologies have the potential to enable seamless and natural human-machine interaction, creating new possibilities for communication, collaboration, and entertainment. The findings will have a significant impact on the development of new ...read more
Related Journals
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Dual-Specificity MAP Kinase Phosphatases as Targets of Cancer Treatment
Anti-Cancer Agents in Medicinal Chemistry Quinone-Based Drugs: An Important Class of Molecules in Medicinal Chemistry
Medicinal Chemistry Vascular Targeting: A New Antitumor Activity
Drug Design Reviews - Online (Discontinued) Pharmacogenetic Aspects of Drug Metabolizing Enzymes in Busulfan Based Conditioning Prior to Allogenic Hematopoietic Stem Cell Transplantation in Children
Current Drug Metabolism Molecular Chaperones as Rational Drug Targets for Parkinsons Disease Therapeutics
CNS & Neurological Disorders - Drug Targets Targeting Angiogenesis in Soft Tissue Sarcomas
Current Angiogenesis (Discontinued) Natural Products Homoharringtonine and Emetine Alkaloids as SARS-CoV-2 Treatment Options
Current Pharmaceutical Design Cationic Liposomes as Non-viral Vector for RNA Delivery in Cancer Immunotherapy
Recent Patents on Drug Delivery & Formulation Wnt Signaling and Prostate Cancer
Current Drug Targets Clinical Trial Update and Novel Therapeutic Approaches for Metastatic Prostate Cancer
Current Medicinal Chemistry Hodgkin Lymphoma in HIV Positive Patients
Current HIV Research Therapeutic Targeting of NLRP3 Inflammasomes by Natural Products and Pharmaceuticals: A Novel Mechanistic Approach for Inflammatory Diseases
Current Medicinal Chemistry Immobilized Using Nanotechnology of Electron-Beam Synthesis Regulators of Progenitor Cells Functions: Remedies of New Generation for Regenerative Medicine
Recent Patents on Regenerative Medicine Novel Therapeutic Approaches in Rheumatoid Arthritis: Role of Janus Kinases Inhibitors
Current Medicinal Chemistry Effect of Non-Steroidal Anti-Inflammatory Drugs on Bone Turnover: An Evidence-Based Review
Reviews on Recent Clinical Trials Sphingolipid Metabolism and Drug Resistance in Hematological Malignancies
Anti-Cancer Agents in Medicinal Chemistry STAT3 Activation in Circulating Monocytes Contributes to Neovascular Age-Related Macular Degeneration
Current Molecular Medicine Subungueal Haemorrhages Following Docetaxel (Taxotere) Treatment
Current Drug Safety Nanomedicine as a Strategy for Natural Compound Delivery to Prevent and Treat Cancers
Current Pharmaceutical Design Immune Checkpoint Inhibitors in Patients with Recurrent Hepatocellular Carcinoma after Liver Transplantation: A Case Report and Literature Review
Current Cancer Drug Targets