Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Classification of Cardiovascular Disease Using AdaBoost Method
https://orcid.org/http://orcid.org/0000-0001-5332-9545
https://orcid.org/http://orcid.org/0000-0001-8189-631X
https://orcid.org/http://orcid.org/0000-0001-6014-1065
The paper is devoted to diagnosing patients with cardiovascular disease. To determine the disease in medical diagnostics, statistical methods are most often used Data Mining, which with large amounts of information and complex relationships can give more accurate estimates, especially with a large number of similar characteristics. The machine learning model for cardiovascular disease classification based on AdaBoost method have been developed using Python programming language. We used dataset of 68783 patients with suspicious of cardiovascular disease. The results of the simulation show enough accuracy for using it in Public Health practice. Implementation of information system can increase diagnosing the cardiovascular disease by medical workers.
Classification of Cardiovascular Disease Using AdaBoost Method
https://orcid.org/http://orcid.org/0000-0001-5332-9545
https://orcid.org/http://orcid.org/0000-0001-8189-631X
https://orcid.org/http://orcid.org/0000-0001-6014-1065
The paper is devoted to diagnosing patients with cardiovascular disease. To determine the disease in medical diagnostics, statistical methods are most often used Data Mining, which with large amounts of information and complex relationships can give more accurate estimates, especially with a large number of similar characteristics. The machine learning model for cardiovascular disease classification based on AdaBoost method have been developed using Python programming language. We used dataset of 68783 patients with suspicious of cardiovascular disease. The results of the simulation show enough accuracy for using it in Public Health practice. Implementation of information system can increase diagnosing the cardiovascular disease by medical workers.
Classification of Cardiovascular Disease Using AdaBoost Method
https://orcid.org/http://orcid.org/0000-0001-5332-9545
https://orcid.org/http://orcid.org/0000-0001-8189-631X
https://orcid.org/http://orcid.org/0000-0001-6014-1065
The paper is devoted to diagnosing patients with cardiovascular disease. To determine the disease in medical diagnostics, statistical methods are most often used Data Mining, which with large amounts of information and complex relationships can give more accurate estimates, especially with a large number of similar characteristics. The machine learning model for cardiovascular disease classification based on AdaBoost method have been developed using Python programming language. We used dataset of 68783 patients with suspicious of cardiovascular disease. The results of the simulation show enough accuracy for using it in Public Health practice. Implementation of information system can increase diagnosing the cardiovascular disease by medical workers.
Classification of Cardiovascular Disease Using AdaBoost Method
Lect. Notes in Networks, Syst.
Arsenyeva, Olga (Herausgeber:in) / Romanova, Tatiana (Herausgeber:in) / Sukhonos, Maria (Herausgeber:in) / Tsegelnyk, Yevgen (Herausgeber:in) / Bazilevych, Kseniia (Autor:in) / Butkevych, Mykola (Autor:in) / Padalko, Halyna (Autor:in)
International Conference on Smart Technologies in Urban Engineering ; 2022 ; Kharkiv, Ukraine
29.11.2022
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Classification of Cardiovascular Disease Using AdaBoost Method
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