Swarm Intelligence Based Technique for Rule Mining in the Medical Domain

Mangat, Veenu

doi:10.5120/796-1131

Cited by 9 publications

(3 citation statements)

References 23 publications

(24 reference statements)

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“…It was found that for strategic decision making, the predictive Apriori algorithm was the best suited to its highest and lowest values. The authors noticed that the limitations of the method were that success of extracting association rules depended on the datasets as some of the datasets were not suited for any kind of association rules [13].…”

Section: Vol 2 (2018) No 4 E-issn : 2549-9904 Issn : 2549-9610mentioning

confidence: 99%

Data Mining Usage and Applications in Health Services

Çifçi

Hussain

2018

JOIV : Int. J. Inform. Visualization

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Data Mining (DM), used to extract large amounts of hidden, valuable, useful information in large quantities and to provide strategic decision support, has created a new perspective on the use of health data. It has become a rapidly growing method of responding to problematic areas of data in large quantities in almost all sections. Although in health services it seems to be slow, a major leap has come to the scene. The aim of this study is to provide a new perspective on decision-making processes by creating an infrastructure for the health data and to provide examples for healthcare workers in the healthcare industry using DM techniques. Forasmuch as, the conceptual framework of data discovery in databases, Data Warehousing, DM, Business Intelligence (BI) has been given. DM applications and usages are given as examples of priority issues and problem areas in the health sector.

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Section: Vol 2 (2018) No 4 E-issn : 2549-9904 Issn : 2549-9610mentioning

confidence: 99%

Data Mining Usage and Applications in Health Services

Çifçi

Hussain

2018

JOIV : Int. J. Inform. Visualization

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“…Detection of brain tumors (Chandraet al [7]), extraction breast cancer patterns (Yeh et al [8]) and classification rule construction for breast cancer data sets (Gandhi et al [9]) are put in this field. With using a hybrid of PSO and ACO, a rulebased system has been proposed by Mangat, for rule mining in medical domain in [10], also a hybrid model for medical data classi¿cation by integrating a case-based reasoning approach and a particle swarm optimization model is developed by Chang et al in [11].…”

Section: Introductionmentioning

confidence: 99%

An ensemble PSO-based approach for diagnosis of coronary artery disease

Hedeshi

Abadeh

2011

2011 International Symposium on Artificial Intelligence and Signal Processing (AISP)

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The leading causes of heart failure are diseases that damage the heart. One of the most well-known diseases that cause heart failure is Coronary Artery Disease. Diagnosis of Coronary Artery Disease is an important medical problem. Many researchers have tried to develop intelligent medical systems to increase the ability of physicians in detecting this disease. Particle Swarm Optimization (PSO) has been successfully applied in data mining field to extract rule based classification systems. A new ensemble PSO-based approach to extract a set of rules for diagnosis of coronary artery disease is presented in this paper. The boosting method considers the cooperation between fuzzy rules that generate with PSO meta-heuristic. We called this approach as "EP-DC". We have evaluated our new classification approach via the well-known Cleveland data set. Results show that the proposed learning method can detect the coronary artery disease with an acceptable accuracy. In addition, the discovered rules have also considerable comprehensibility.

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“…Detection of brain tumors (Chandraet al [7]), extracting breast cancer patterns (Yeh et al [8]) and classification rule construction for breast cancer data sets (Gandhi et al [9]) are put in this field. using a combination of PSO and ACO, a rule-based system has been proposed by Mangat for rule mining in medical domain in [10], also a hybrid model for medical data classification by integrating a case-based reasoning approach and a particle swarm optimization model is developed by Chang et al in [11].…”

Section: Introductionmentioning

confidence: 99%

An expert system working upon an ensemble PSO-based approach for diagnosis of coronary artery disease

Hedeshi

Abadeh

2011

2011 18th Iranian Conference of Biomedical Engineering (ICBME)

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It is evident that usage of data mining methods in disease diagnosis has been increasing gradually. In this paper, diagnosis of Coronary Artery Disease, which is one of the most well-known diseases that cause heart failure, was conducted with such a data mining system. Many researchers have attempted to develop a medical expert system to increase the ability of physicians in detecting this disease. This paper proposes a new ensemble PSO-based approach to extract a set of rules for diagnosis of coronary artery disease. The new presented boosting mechanism considers the cooperation between generated fuzzy if-then rules using the PSO metaheuristic. We have evaluated our new classification approach using the well-known Cleveland data set. Results indicate that the proposed learning method can detect the coronary artery disease with an acceptable accuracy. In addition, the extracted fuzzy rules have significant interpretability either.

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Swarm Intelligence Based Technique for Rule Mining in the Medical Domain

Cited by 9 publications

References 23 publications

Data Mining Usage and Applications in Health Services

Data Mining Usage and Applications in Health Services

An ensemble PSO-based approach for diagnosis of coronary artery disease

An expert system working upon an ensemble PSO-based approach for diagnosis of coronary artery disease

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