A fuzzy expert system design for diagnosis of prostate cancer

Author(s):  
Ismail Saritas ◽  
Novruz Allahverdi ◽  
Ibrahim Unal Sert
2020 ◽  
Vol 16 (01) ◽  
pp. 163-176
Author(s):  
Juthika Mahanta ◽  
Subhasis Panda

A fuzzy expert system (FES) for the prediction of prostate cancer (PC) is prescribed in this paper. Age, prostate-specific antigen (PSA), prostate volume (PV) and [Formula: see text] Free PSA ([Formula: see text]FPSA) are fed as inputs into the FES and prostate cancer risk (PCR) is obtained as the output. Using knowledge-based rules in Mamdani type inference method the output is calculated. If PCR [Formula: see text], then the patient shall be advised to go for a biopsy test for confirmation. The efficacy of the designed FES is tested against a clinical dataset. The true prediction for all the patients turns out to be [Formula: see text] whereas only for positive biopsy cases it rises to [Formula: see text]. This simple yet effective FES can be used as supportive tool for decision-making in medical diagnosis.


2008 ◽  
Vol 202 (1) ◽  
pp. 78-85 ◽  
Author(s):  
Maria José de Paula Castanho ◽  
Laécio Carvalho de Barros ◽  
Akebo Yamakami ◽  
Laércio Luis Vendite

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