Art

J-GLOBAL ID：202302266627079827   Reference number：23A1842736

Effective Heart Disease Prediction Using Machine Learning Techniques

機械学習技術を用いた効果的な心臓病予測【JST・京大機械翻訳】

Author (4)： Bhatt Chintan M. (Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382007, India) ,  Patel Parth (Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382007, India) ,  Ghetia Tarang (Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382007, India) ,  Mazzeo Pier Luigi (Institute of Applied Sciences and Intelligent Systems, National Research Council of Italy, 73100 Lecce, Italy)
Material： Algorithms (Web)
Volume： 16  Issue： 2  Page： 88  Publication year： 2023 
JST Material Number： U7130A  ISSN： 1999-4893  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： The diagnosis and prognosis of...

Register(free) or Log In to access     To see more with JDream III (charged).   {{ this.onShowAbsJLink("http://jdream3.com/lp/jglobal/index.html?docNo=23A1842736&from=J-GLOBAL&jstjournalNo=U7130A") }}

Thesaurus term： algorithm ,  optimization ,  *heart ,  lethality ,  clustering ,  cardiovascular disease ,  *heart disease ,  decision tree ,  computer algorithm ,  application program ,  prognosis ,  multilayer perceptron ,  area under the blood concentration time curve ,  *machine learning
Semi thesaurus term： ランダムフォレスト ,  *機械学習技術 , 【Automatic Indexing@JST】

Author keywords (6)： heart disease ,  machine learning ,  k-modes ,  classification ,  multilayer perceptron ,  model evaluation

JST classification (2)： Artificial intelligence  (JE08000Z) ,  Cardiovascular system diagnosis  (GJ02000V)

Reference (35)：

• Estes, C.; Anstee, Q.M.; Arias-Loste, M.T.; Bantel, H.; Bellentani, S.; Caballeria, J.; Colombo, M.; Craxi, A.; Crespo, J.; Day, C.P.; et al. Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016-2030. J. Hepatol. 2018, 69, 896-904.
• Drożdż, K.; Nabrdalik, K.; Kwiendacz, H.; Hendel, M.; Olejarz, A.; Tomasik, A.; Bartman, W.; Nalepa, J.; Gumprecht, J.; Lip, G.Y.H. Risk factors for cardiovascular disease in patients with metabolic-associated fatty liver disease: A machine learning approach. Cardiovasc. Diabetol. 2022, 21, 240.
• Murthy, H.S.N.; Meenakshi, M. Dimensionality reduction using neuro-genetic approach for early prediction of coronary heart disease. In Proceedings of the International Conference on Circuits, Communication, Control and Computing, Bangalore, India, 21-22 November 2014; pp. 329-332.
• Benjamin, E.J.; Muntner, P.; Alonso, A.; Bittencourt, M.S.; Callaway, C.W.; Carson, A.P.; Chamberlain, A.M.; Chang, A.R.; Cheng, S.; Das, S.R.; et al. Heart disease and stroke statistics-2019 update: A report from the American heart association. Circulation 2019, 139, e56-e528.
• Shorewala, V. Early detection of coronary heart disease using ensemble techniques. Inform. Med. Unlocked 2021, 26, 100655.

Terms in the title (3)： 機械学習技術 ,  心臓病 ,  予測