Survey on medical diagnosis using data mining techniques

Sumalatha, G.; Muniraj, N. J. R.

doi:10.1109/icoiss.2013.6678433

Cited by 8 publications

(5 citation statements)

References 14 publications

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“…Algorithm 1 shows the BA (adapted from [19]): First, the frequency " ", velocity " ", and position " " are initiated for every bat" . Every time phase ", the highest digit of reiteration, "a" virtual bat's activity is set by updating the position and velocity using (1)…”

Section: Bat Algorithm For Feature Selectionmentioning

confidence: 99%

“…where "is the randomly created digit during the period [1,0]. The coefficient" ( )"is equivalent to variable" "for bat at time phase .…”

Section: Bat Algorithm For Feature Selectionmentioning

confidence: 99%

“…In the medical field, data mining plays an important role in the prediction of diseases. Data mining uses machine learning, artificial intelligence, and statistical power to develop highly accurate predictive models for critical domains [1]. Cancer is a topic of interest in the medical field and the primary cause of mortality worldwide [2].…”

Section: Introductionmentioning

confidence: 99%

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Hybrid bat-ant colony optimization algorithm for rule-based feature selection in health care

Sagban

Marhoon

Alubady

2020

IJECE

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Rule-based classification in the field of health care using artificial intelligence provides solutions in decision-making problems involving different domains. An important challenge is providing access to good and fast health facilities. Cervical cancer is one of the most frequent causes of death in females. The diagnostic methods for cervical cancer used in health centers are costly and time-consuming. In this paper, bat algorithm for feature selection and ant colony optimization-based classification algorithm were applied on cervical cancer data set obtained from the repository of the University of California, Irvine to analyze the disease based on optimal features. The proposed algorithm outperforms other methods in terms of comprehensibility and obtains better results in terms of classification accuracy.

show abstract

Section: Bat Algorithm For Feature Selectionmentioning

confidence: 99%

“…where "is the randomly created digit during the period [1,0]. The coefficient" ( )"is equivalent to variable" "for bat at time phase .…”

Section: Bat Algorithm For Feature Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hybrid bat-ant colony optimization algorithm for rule-based feature selection in health care

Sagban

Marhoon

Alubady

2020

IJECE

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“…The medical domain consists of a considerable amount of data, including complete human genetic code information; clinical information on the history of patients, diagnosis, inspection, and treatment; and drug management information. Data mining can be applied in the medical field to analyze medical data, extract implicit valuable information, provide correct diagnosis and treatment, and study the genetic law of human diseases and health [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Using k-dependence causal forest to mine the most significant dependency relationships among clinical variables for thyroid disease diagnosis

et al. 2017

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Numerous data mining models have been proposed to construct computer-aided medical expert systems. Bayesian network classifiers (BNCs) are more distinct and understandable than other models. To graphically describe the dependency relationships among clinical variables for thyroid disease diagnosis and ensure the rationality of the diagnosis results, the proposed k-dependence causal forest (KCF) model generates a series of submodels in the framework of maximum spanning tree (MST) and demonstrates stronger dependence representation. Friedman test on 12 UCI datasets shows that KCF has classification accuracy advantage over the other state-of-the-art BNCs, such as Naive Bayes, tree augmented Naive Bayes, and k-dependence Bayesian classifier. Our extensive experimental comparison on 4 medical datasets also proves the feasibility and effectiveness of KCF in terms of sensitivity and specificity.

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“…Big data playing an important role in the field of health care [19]. It stores patient details doctor information pharmacy details medical laboratory information list of different diseases and diagnosis information the process of storing and extracting of such information is a critical task for database using traditional system which deals with small datasets to become such issues big data archived some goal in predicting diseases and in diagnosing them [20].…”

Section: Healthcarementioning

confidence: 99%

Privacy and Security in Big Data Management

Rannels¹,

Falconieri²,

Phillips³

et al. 2018

IJRTER

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Abstract-Finding new ways to take advantage of big data, small or big organizations need high security techniques end efficient policies to guarantee their systems. In big data, it is very difficult to store data and analyse these data with conventional techniques. It is though that the traditional mechanisms are not efficient on big data security and privacy challenges. Different challenges include Hadoop security, cloud security and monitoring and auditing, etc. Big data deals with different data formats, data collection done from different sources, streaming of data may cause security problems the existing systems led to the violation of the individual privacy control. Data should be shared in a secure environment without violating people's privacy to overcome such complex issues, it is necessary to implement some set of rules and regulations in performing data sharing, authentication process, in generating personal information, and misusing of the system. With respect to these problems, proposed system introduced some mechanism challenging security and privacy issues for both user and application oriented.

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Survey on medical diagnosis using data mining techniques

Cited by 8 publications

References 14 publications

Hybrid bat-ant colony optimization algorithm for rule-based feature selection in health care

Hybrid bat-ant colony optimization algorithm for rule-based feature selection in health care

Using k-dependence causal forest to mine the most significant dependency relationships among clinical variables for thyroid disease diagnosis

Privacy and Security in Big Data Management

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