Abstract
Fuzzy logic has different approaches for enhancing personal health care delivery. Currently, breast cancer is rated as the second leading cause of death among women. Previous studies using fuzzy logic were directed at reoccurrence/survivability. However, there is need for early identification of the predisposing factors of the disease and its elimination. This study focuses on developing a Mobile-based Fuzzy Expert System (MFES) to predict an individual risk of initial cancer growth. The predisposing risk factors of breast cancer were elicited from four domain experts through direct contact; this was used to generate the fuzzy rules. The fuzzy inference approach was employed to formulate the membership functions.Mamdani approach was used for the system design. The system accommodates imprecision, tolerance and uncertainty to achieve tractability, robustness and low cost. Java expert system shell running on Android operating system was used to achieve the mobile technology aspect. For the purpose of system evaluation, 2500 data were collected from two health care centers in Nigeria using random sampling. The result indicated that the fact elicited from the experts served as range values for the 12 risk factors for fuzzification of the input and thus, 36 rules were generated. The rules were used for the system development. The developed MFES recorded 96% accuracy. It is therefore recommended that MFES be used to detect breast cancer risk levels early enough. The main contribution of this work is to reduce the incidence rate in contrast to the existing methods currently applied in the diagnosis of breast cancer. Keywords : Soft Computing, Fuzzy Set, Breast Cancer, Risk Factors, Membership Functions
Highlights
Information Technology (IT), can play a key role in enhancing and enabling health care systems, when linked to specific needs
In modelling real life situation, like breast cancer, the relationships that exist between input variables and output and the connection between each indentified input variables are somewhat complex, it is grim to express interactive relationships
Fuzzy inference greatly simplifies and fasttracks the computing procedure for a real life situation modelling because most optimal result from accurate mathematical expressions is tough to get
Summary
Information Technology (IT), can play a key role in enhancing and enabling health care systems, when linked to specific needs. The initiation of various types of mobile portable computer devices – smartphones has influenced an appreciated positive impact in many works of life which includes the health sector. This has been influenced by the increasing excellence and availability of application software in the health sector [2]. Assessment Tool which have not met the need in the health sector These models did not explore detail risk factors for breast cancer growth, and detail fuzzy rules were not explored as well. Most of the mobile health calculators for breast cancer prognosis are not user friendly, were more on after growth prognosis and are not readily available for personal use
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