Analytical fuzzy approach to biological data analysis.
Saudi J Biol Sci
; 24(3): 563-573, 2017 Mar.
Article
de En
| MEDLINE
| ID: mdl-28386181
ABSTRACT
The assessment of the physiological state of an individual requires an objective evaluation of biological data while taking into account both measurement noise and uncertainties arising from individual factors. We suggest to represent multi-dimensional medical data by means of an optimal fuzzy membership function. A carefully designed data model is introduced in a completely deterministic framework where uncertain variables are characterized by fuzzy membership functions. The study derives the analytical expressions of fuzzy membership functions on variables of the multivariate data model by maximizing the over-uncertainties-averaged-log-membership values of data samples around an initial guess. The analytical solution lends itself to a practical modeling algorithm facilitating the data classification. The experiments performed on the heartbeat interval data of 20 subjects verified that the proposed method is competing alternative to typically used pattern recognition and machine learning algorithms.
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Type d'étude:
Prognostic_studies
Langue:
En
Journal:
Saudi J Biol Sci
Année:
2017
Type de document:
Article
Pays d'affiliation:
Chine
Pays de publication:
ARABIA SAUDITA
/
ARÁBIA SAUDITA
/
SA
/
SAUDI ARABIA