Digitale Bibliotheek
Sluiten Bladeren door artikelen uit een tijdschrift
 
<< vorige    volgende >>
     Tijdschrift beschrijving
       Alle jaargangen van het bijbehorende tijdschrift
         Alle afleveringen van het bijbehorende jaargang
           Alle artikelen van de bijbehorende aflevering
                                       Details van artikel 26 van 127 gevonden artikelen
 
 
  Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks
 
 
Titel: Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks
Auteur: K.Srinivas
B.Kavihta Rani
Dr. A.Govrdhan
Verschenen in: International journal on computer science and engineering
Paginering: Jaargang 2 (2010) nr. 2 pagina's 250-255
Jaar: 2010
Inhoud: The healthcare environment is generally perceived as being ‘information rich’ yet ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain. Valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, we briefly examine the potential use of classification based data mining techniques such as Rule based, Decision tree, Naïve Bayes and Artificial Neural Network to massive volume of healthcare data. The healthcare industrycollects huge amounts of healthcare data which, unfortunately, are not “mined” to discover hidden information. For data preprocessing and effective decision making One Dependency Augmented Naïve Bayes classifier (ODANB) and naive credal classifier 2 (NCC2) are used. This is an extension of naive Bayes to imprecise probabilities that aims at delivering robust classifications also when dealing with small or incomplete data sets. Discovery of hidden patterns and relationships often goes unexploited. Using medical profiles such as age, sex, blood pressure and blood sugar it can predict the likelihood of patients getting a heart disease. It enables significant knowledge, e.g. patterns, relationships between medical factors related to heart disease, to be established.
Uitgever: Engg Journals Publications (provided by DOAJ)
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details van artikel 26 van 127 gevonden artikelen
 
<< vorige    volgende >>
 
 Koninklijke Bibliotheek - Nationale Bibliotheek van Nederland