Fuzzy Logic-Based Predictive Model for the Risk of Sexually Transmitted Diseases (STD) in Nigeria

Autor:	Adanze Onyenonachi Asinobi, F.A. Oladeji, Jeremiah Ademola Balogun, Olayinka Olufunmilayo Olusanya, Olajide Blessing Olajide, Peter Adebayo Idowu
Rok vydání:	2020
Předmět:	Computer science business.industry Artificial intelligence Machine learning computer.software_genre business computer Fuzzy logic
Zdroj:	International Journal of Big Data and Analytics in Healthcare. 5:38-57
ISSN:	2379-7371 2379-738X
DOI:	10.4018/ijbdah.2020070103
Popis:	This study developed a classification model for monitoring the risk of sexually transmitted diseases (STDs) among females using information about non-invasive risk factors. Structured interview with physicians was done in order to identify the risk factors that are associated with the risk of STDs in Nigeria. The model was simulated using the fuzzy logic toolbox accessible in the MATLAB® R2015a Software. The results showed that nine non-invasive risk factors were associated with the risk of STDs among female patients in Nigeria. Two, three, and four triangular membership functions were appropriate for the formulation of the linguistic variables of the factors while the target risk was formulated using four triangular membership functions for the linguistic variables namely no risk, low risk, moderate risk, and high risk. The study concluded that the fuzzy logic model approach was adequate for predicting the risk of STDs based on the knowledge of the risk factors.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5d1dd75e004ab8f2b9d6d104a0dcda10 https://doi.org/10.4018/ijbdah.2020070103 Zobrazit plný text záznamu