An integrated review on machine learning approaches for heart disease prediction: Direction towards future research gaps

Vellameeran, Fathima Aliyar; Brindha, Thomas

doi:10.1515/bams-2020-0069

Artykuł - szczegóły

Tytuł artykułu

An integrated review on machine learning approaches for heart disease prediction: Direction towards future research gaps

Autorzy

Vellameeran Fathima Aliyar , Brindha Thomas

Wybrane pełne teksty z tego czasopisma

Identyfikatory

DOI

10.1515/bams-2020-0069

Warianty tytułu

Konferencja

4th Jagiellonian Symposium on Advances in Particle Physics and Medicine, Krakow, 10-15 July 2022

Języki publikacji

Abstrakty

Objectives: To make a clear literature review on state-ofthe-art heart disease prediction models. Methods: It reviews 61 research papers and states the significant analysis. Initially, the analysis addresses the contributions of each literature works and observes the simulation environment. Here, different types of machine learning algorithms deployed in each contribution. In addition, the utilized dataset for existing heart disease prediction models was observed. Results: The performance measures computed in entire papers like prediction accuracy, prediction error, specificity, sensitivity, f-measure, etc., are learned. Further, the best performance is also checked to confirm the effectiveness of entire contributions. Conclusions: The comprehensive research challenges and the gap are portrayed based on the development of intelligent methods concerning the unresolved challenges in heart disease prediction using data mining techniques.

Słowa kluczowe

data mining health care sector heart disease prediction machine learning algorithms performance analysis research gaps

Wydawca

Uniwersytet Jagielloński - Collegium Medicum
Index Copernicus Sp. z o.o.

Czasopismo

Bio-Algorithms and Med-Systems

Rocznik

2022

Tom

Vol. 18, no. 1

Strony

69--83

Opis fizyczny

Bibliogr. 97 poz., rys., tab.

Twórcy

autor

Vellameeran Fathima Aliyar

fathi.avm@gmail.com

Department of Computer Applications, College of Engineering, Vadakara, Kerala, India

autor

Brindha Thomas

Department of Information Technology, Noorul Islam Centre for Higher Education, Kanyakumari, India

Bibliografia

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Uwagi

Opublikowane przez Sciendo. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

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Bibliografia

Identyfikator YADDA

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