Bayesian network model for diagnosis of psychiatric diseases

Curiac, Daniel-Ioan; Vasile, Gabriel; Baniaș, Ovidiu; Voloşencu, Constantin; Albu, Adriana

doi:10.1109/iti.2009.5196055

Cited by 39 publications

(24 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In terms of prediction and decision making, Data mining techniques have substantial expansion in medical industry with respect to various diseases like diabetes, heart disease, liver diseases, cancer and others. Predicate the probability of a psychiatric patient on the basis detected symptoms using BBN Bayesian networks [7].…”

Section: Associationmentioning

confidence: 99%

Survey of Data Mining Techniques used in Healthcare Domain

Patel¹,

Patel²

2016

IJIST

View full text Add to dashboard Cite

Health care industry produces enormous quantity of data that clutches complex information relating to patients and their medical conditions. Data mining is gaining popularity in different research arenas due to its infinite applications and methodologies to mine the information in correct manner. Data mining techniques have the capabilities to discover hidden patterns or relationships among the objects in the medical data. In last decade, there has been increase in usage of data mining techniques on medical data for determining useful trends or patterns that are used in analysis and decision making. Data mining has an infinite potential to utilize healthcare data more efficiently and effectually to predict different kind of disease. This paper features various Data Mining techniques such as classification, clustering, association and also highlights related work to analyse and predict human disease.

show abstract

Section: Associationmentioning

confidence: 99%

Survey of Data Mining Techniques used in Healthcare Domain

Patel¹,

Patel²

2016

IJIST

View full text Add to dashboard Cite

show abstract

“…In this research, it has been found that BBN plays a very important role in medical decision making process in order to predicate the probability of a psychiatric patient on the basis detected symptoms [64].…”

Section: Classification Techniques Examples In Healthcarementioning

confidence: 99%

Techniques of Data Mining In Healthcare: A Review

Ahmad¹,

Qamar²,

Rizvi³

2015

IJCA

View full text Add to dashboard Cite

Data mining is gaining popularity in disparate research fields due to its boundless applications and approaches to mine the data in an appropriate manner. Owing to the changes, the current world acquiring, it is one of the optimal approach for approximating the nearby future consequences. Along with advanced researches in healthcare monstrous of data are available, but the main difficulty is how to cultivate the existing information into a useful practices. To unfold this hurdle the concept of data mining is the best suited. Data mining have a great potential to enable healthcare systems to use data more efficiently and effectively. Hence, it improves care and reduces costs. This paper reviews various Data Mining techniques such as classification, clustering, association, regression in health domain. It also highlights applications, challenges and future work of Data Mining in healthcare.

show abstract

“…Curiac et al [25]., analyze the psychiatric patient data using BBN in making significant decision regarding patient health suffering from psychiatric disease and performed experiment on real data obtain from Lugoj Municipal Hospital.…”

Section: Related Workmentioning

confidence: 99%

A Survey on Medical Text Mining

Nair¹,

Sindhu²

2014

IJCA

View full text Add to dashboard Cite

Medical diagnosis is considered as an important yet complicated task that needs to be executed accurately and efficiently. The automation of this system will be very useful for the medical field. Due to recent technology advances, large masses of medical data are available. These large data contain valuable information for diagnosing diseases. Text mining techniques are using to extract useful patterns from these mass data. It provides a user-oriented approach to the novel and hidden patterns in the data. This paper intends to provide the survey of various medical text mining techniques used in medical field. The purpose of this survey is to obtain a most suitable text mining technique for the medical data.

show abstract

Bayesian network model for diagnosis of psychiatric diseases

Cited by 39 publications

References 4 publications

Survey of Data Mining Techniques used in Healthcare Domain

Survey of Data Mining Techniques used in Healthcare Domain

Techniques of Data Mining In Healthcare: A Review

A Survey on Medical Text Mining

Contact Info

Product

Resources

About