Fuzzy soft set theory: Application of classification rules in decision making during medical diagnosis

• Published in: Journal of intelligent & fuzzy systems Vol. 41; no. 1; pp. 2377 - 2385
• Main Authors: Aziz, Fehmi, Tahir, Faheem, Midhat, Sadia, Naz, Shafaq, Qureshi, Naveeda Akhtar
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2021; Sage Publications Ltd
• Subjects: Algorithms; Body size; Decision making; Decision theory; Diagnosis; Fuzzy set theory; Fuzzy sets; Hemoglobin; Medical diagnosis; Medical research; Modelling; Rural areas; soft set; maternal anemia; fuzzy set; Medical diagnosis; BMI
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-190452

 Present study is an interdisciplinary approach towards rapid and efficient medical diagnosis. The research articulated on data set of cross-sectional study of pregnant females dwelling rural area of Pakistan. The prognosis of gestational wellbeing followed through analyzing heterogenic medical information to develop a holistic picture of ongoing pregnancy. Therefore, for rapid medical diagnosis and precision in decision-making, Fuzzy Soft Set (denoted as FSS) theory selected to develop an algorithm. The algorithm constructed as single point, multipoint and cumulative diagnosis for predicting health status with respect of Hemoglobin, Body Mass Index and Random Glucose Concentration (Respectively denoted as Hb, BMI and RGC) of subjects under study. We successfully proposed novel approach for complex modeling and provision of algorithm for medical diagnosis. The algorithms successfully dealt with analyzing diversely attributed detailed medical tests/reports as input. The output of complex modeling effectively served efficient decision-making in predicting gestational wellbeing.