Enhancing Toddler Health Management: A Fuzzy Mamdani Decision Support System in Pediatric Healthcare
Keywords:
Pediatric Healthcare, Fuzzy Logic, Decision Support System, Toddler Health, Mamdani ReasoningAbstract
This research endeavors to develop a sophisticated Decision Support System (DSS) employing Fuzzy Mamdani reasoning tailored for toddler health management. Utilizing fuzzy logic principles, the system aims to revolutionize pediatric healthcare practices by offering precision, personalized care, and informed decision-making support. The DSS integrates linguistic variables, fuzzy sets, and Mamdani-type fuzzy reasoning to navigate the complexities of toddler health. By accommodating imprecise data, it provides nuanced assessments, enabling caregivers and healthcare professionals to make informed decisions regarding health concerns. Throughout the research, the system demonstrates strengths in precision assessments and personalized recommendations, enhancing its relevance in caregiving and healthcare decision-making. However, challenges in interpretability, data dependency, and implementation complexities surfaced, prompting the need for ongoing refinement and validation against clinical expertise. The implications of this research extend to real-world applications encompassing clinical settings, home healthcare, public health initiatives, and healthcare education. It signifies a significant stride towards transforming toddler healthcare, fostering better health outcomes and well-being for our youngest population.
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