FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3039234028> ?p ?o ?g. }

• W3039234028 endingPage "105635" @default.
• W3039234028 startingPage "105635" @default.
• W3039234028 abstract "Early detection of heart disease is an important challenge since 17.3 million people yearly lose their lives due to heart diseases. Besides, any error in diagnosis of cardiac disease can be dangerous and risks an individual's life. Accurate diagnosis is therefore critical in cardiology. Data Mining (DM) classification techniques have been used to diagnosis heart diseases but still limited by some challenges of data quality such as inconsistencies, noise, missing data, outliers, high dimensionality and imbalanced data. Data preprocessing (DP) techniques were therefore used to prepare data with the goal of improving the performance of heart disease DM based prediction systems. The purpose of this study is to review and summarize the current evidence on the use of preprocessing techniques in heart disease classification as regards: (1) the DP tasks and techniques most frequently used, (2) the impact of DP tasks and techniques on the performance of classification in cardiology, (3) the overall performance of classifiers when using DP techniques, and (4) comparisons of different combinations classifier-preprocessing in terms of accuracy rate. A systematic literature review is carried out, by identifying and analyzing empirical studies on the application of data preprocessing in heart disease classification published in the period between January 2000 and June 2019. A total of 49 studies were therefore selected and analyzed according to the aforementioned criteria. The review results show that data reduction is the most used preprocessing task in cardiology, followed by data cleaning. In general, preprocessing either maintained or improved the performance of heart disease classifiers. Some combinations such as (ANN + PCA), (ANN + CHI) and (SVM + PCA) are promising terms of accuracy. However the deployment of these models in real-world diagnosis decision support systems is subject to several risks and limitations due to the lack of interpretation." @default.
• W3039234028 created "2020-07-10" @default.
• W3039234028 creator A5000218612 @default.
• W3039234028 creator A5031769056 @default.
• W3039234028 creator A5064762344 @default.
• W3039234028 date "2020-10-01" @default.
• W3039234028 modified "2023-10-01" @default.
• W3039234028 title "Data preprocessing for heart disease classification: A systematic literature review" @default.
• W3039234028 cites W1509813225 @default.
• W3039234028 cites W1524157153 @default.
• W3039234028 cites W1742842785 @default.
• W3039234028 cites W1965587486 @default.
• W3039234028 cites W1977177161 @default.
• W3039234028 cites W1977185509 @default.
• W3039234028 cites W1981653086 @default.
• W3039234028 cites W1981976602 @default.
• W3039234028 cites W1989022033 @default.
• W3039234028 cites W1989344766 @default.
• W3039234028 cites W1999798506 @default.
• W3039234028 cites W2005422872 @default.
• W3039234028 cites W2005791255 @default.
• W3039234028 cites W2009977195 @default.
• W3039234028 cites W2028470267 @default.
• W3039234028 cites W2029295760 @default.
• W3039234028 cites W2044480702 @default.
• W3039234028 cites W2047266047 @default.
• W3039234028 cites W2053481403 @default.
• W3039234028 cites W2061669177 @default.
• W3039234028 cites W2065591343 @default.
• W3039234028 cites W2079125934 @default.
• W3039234028 cites W2083192087 @default.
• W3039234028 cites W2087264237 @default.
• W3039234028 cites W2091255497 @default.
• W3039234028 cites W2092964187 @default.
• W3039234028 cites W2108044541 @default.
• W3039234028 cites W2122111042 @default.
• W3039234028 cites W2125654608 @default.
• W3039234028 cites W2126326838 @default.
• W3039234028 cites W2132091485 @default.
• W3039234028 cites W2132513961 @default.
• W3039234028 cites W2137687977 @default.
• W3039234028 cites W2140898374 @default.
• W3039234028 cites W2141018154 @default.
• W3039234028 cites W2144836313 @default.
• W3039234028 cites W2151205988 @default.
• W3039234028 cites W2164117960 @default.
• W3039234028 cites W2164330572 @default.
• W3039234028 cites W2165772152 @default.
• W3039234028 cites W2217357966 @default.
• W3039234028 cites W2344731017 @default.
• W3039234028 cites W2391474792 @default.
• W3039234028 cites W2500519874 @default.
• W3039234028 cites W2519289376 @default.
• W3039234028 cites W2528171117 @default.
• W3039234028 cites W2548125779 @default.
• W3039234028 cites W2562319768 @default.
• W3039234028 cites W2567666657 @default.
• W3039234028 cites W2568394902 @default.
• W3039234028 cites W2591753428 @default.
• W3039234028 cites W2607320737 @default.
• W3039234028 cites W2616609740 @default.
• W3039234028 cites W2746293078 @default.
• W3039234028 cites W2755507768 @default.
• W3039234028 cites W2755582817 @default.
• W3039234028 cites W2764769393 @default.
• W3039234028 cites W2765722795 @default.
• W3039234028 cites W2769042349 @default.
• W3039234028 cites W2778545923 @default.
• W3039234028 cites W2780276225 @default.
• W3039234028 cites W2789532252 @default.
• W3039234028 cites W2790444357 @default.
• W3039234028 cites W2800769566 @default.
• W3039234028 cites W2895734781 @default.
• W3039234028 cites W2900003150 @default.
• W3039234028 cites W2900794383 @default.
• W3039234028 cites W2904426934 @default.
• W3039234028 cites W2919115771 @default.
• W3039234028 cites W2920679031 @default.
• W3039234028 cites W2963428668 @default.
• W3039234028 cites W2963565281 @default.
• W3039234028 cites W2967246721 @default.
• W3039234028 cites W323404752 @default.
• W3039234028 cites W4236137412 @default.
• W3039234028 doi "https://doi.org/10.1016/j.cmpb.2020.105635" @default.
• W3039234028 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32652383" @default.
• W3039234028 hasPublicationYear "2020" @default.
• W3039234028 type Work @default.
• W3039234028 sameAs 3039234028 @default.
• W3039234028 citedByCount "45" @default.
• W3039234028 countsByYear W30392340282021 @default.
• W3039234028 countsByYear W30392340282022 @default.
• W3039234028 countsByYear W30392340282023 @default.
• W3039234028 crossrefType "journal-article" @default.
• W3039234028 hasAuthorship W3039234028A5000218612 @default.
• W3039234028 hasAuthorship W3039234028A5031769056 @default.
• W3039234028 hasAuthorship W3039234028A5064762344 @default.
• W3039234028 hasConcept C10551718 @default.
• W3039234028 hasConcept C119857082 @default.

• next