Title :
The parametric s-functions and the perceptron in gastric cancer surgery decision making
Author :
Rakus-Andersson, Elisabeth
Author_Institution :
Dept. of Math. & Sci., Blekinge Inst. of Technol., Karlskrona, Sweden
Abstract :
In the current paper we mathematically try to support the medical operation decision made for the sake of patients suffering from gastric cancer. We involve the linear model of the simple neural perceptron to distinguish between two decision states determined as “operate” contra “do not operate”. The perceptron input signals are proposed to be given as codes of levels of the most decisive biological markers, considered in surgery decision making. To find the level intervals, tied to the codes, we introduce a procedure of level fuzzification by a family of parametric membership functions.
Keywords :
cancer; decision making; fuzzy set theory; surgery; biological markers; gastric cancer surgery decision making; level fuzzification; linear model; medical operation decision; parametric membership functions; parametric s-functions; simple neural perceptron; Biomarkers; Cancer; Fuzzy sets; Medical diagnostic imaging; Neurons; Surgery; Vectors; gastric cancer; operation decision; parametric s-function; perceptron;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6251321