ARTIFICIAL NEURAL NETWORK APPROACH FOR OBESITY-HYPERTENSION CLASSIFICATION

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

Postolache, O (Author) Other; Joaquim Mendes (Author) FEUP; Postolache, G (Author) Other; Girao, PS (Author) Other

Conference proceedings International

Title: ARTIFICIAL NEURAL NETWORK APPROACH FOR OBESITY-HYPERTENSION CLASSIFICATION

Pages: 514-520

BIOSTEC 2009 - Second International Joint Conference on Biomedical Engineering Systems and Technologies

Vila Nova de Gaia, Portugal, 14 a 17 de Janeiro de 2009

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 0 Citations

Other information

Authenticus ID: P-003-PA6

Abstract (EN): One of the newest targets of public health is management of obesity-hypertension. In this paper is presented the use of an artificial neural network based model for objective classification of obesity-hypertension. Different neural network architectures as part of hybrid processing scheme including comparators and competitive processing blocks were developed and tested. The neural network functionality is the classification of the individuals according to the obesity risks. The results show that the neural network classifier is consistent with the standard criteria suggested by the obesity and hypertension guidelines.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7