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Prediction of death rates for cardiovascular diseases and cancers.
Gaidai, Oleg; Xing, Yihan; Balakrishna, Rajiv; Sun, Jiayao; Bai, Xiaolong.
Afiliación
  • Gaidai O; Shanghai Engineering Research Center of Marine Renewable Energy, College of Engineering Science and Technology Shanghai Ocean University Shanghai China.
  • Xing Y; Department of Mechanical and Structural Engineering and Materials Science University of Stavanger Stavanger Norway.
  • Balakrishna R; Department of Mechanical and Structural Engineering and Materials Science University of Stavanger Stavanger Norway.
  • Sun J; School of Naval Architecture & Ocean Engineering Jiangsu University of Science and Technology Zhenjiang China.
  • Bai X; School of Naval Architecture & Ocean Engineering Jiangsu University of Science and Technology Zhenjiang China.
Cancer Innov ; 2(2): 140-147, 2023 Apr.
Article en En | MEDLINE | ID: mdl-38090058
ABSTRACT

Background:

To estimate cardiovascular and cancer death rates by regions and time periods.

Design:

Novel statistical methods were used to analyze clinical surveillance data.

Methods:

A multicenter, population-based medical survey was performed. Annual recorded deaths from cardiovascular diseases were analyzed for all 195 countries of the world. It is challenging to model such data; few mathematical models can be applied because cardiovascular disease and cancer data are generally not normally distributed.

Results:

A novel approach to assessing the biosystem reliability is introduced and has been found to be particularly suitable for analyzing multiregion environmental and healthcare systems. While traditional methods for analyzing temporal observations of multiregion processes do not deal with dimensionality efficiently, our methodology has been shown to be able to cope with this challenge.

Conclusions:

Our novel methodology can be applied to public health and clinical survey data.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Cancer Innov Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Cancer Innov Año: 2023 Tipo del documento: Article