Calf strains are a common injury among athletes and active individuals, characterized by pain, swelling, and functional impairment. Accurate diagnosis is crucial for effective treatment and rehabilitation. Traditional diagnostic methods rely heavily on clinical expertise and subjective assessment, leading to potential inconsistencies. This paper presents a novel approach to diagnosing calf strains by integrating traditional fuzzy rules with a multi-agent system (MAS) fuzzy rules framework. Fuzzy logic provides a robust mechanism for handling the imprecision and variability inherent in clinical data, while the MAS facilitate efficient data processing and collaborative decision-making. The multi agent system was developed using a comprehensive dataset of 1,000 patient records, including clinical findings, physical examination results, and imaging data. Traditional fuzzy rules were formulated based on expert knowledge and validated through iterative testing. Concurrently, a multi-agent system was designed to simulate the roles of various medical professionals, ensuring dynamic interaction and data integration. The performance of the traditional fuzzy rules was compared with the MAS fuzzy rules in terms of diagnostic accuracy, sensitivity, specificity, and computational efficiency

Calf strain, Fuzzy rules, Multi-agent system, Medical diagnostics, Clinical data, Musculoskeletal injury

In conclusion, the integration of traditional fuzzy rules and a multi-agent system (MAS) framework demonstrates promising results for diagnosing calf strains. The combined approach enhances diagnostic accuracy and efficiency, as evidenced by high agreement in diagnoses between traditional fuzzy logic and MAS. The study underscores the effectiveness of MAS in collaborative decision-making and data integration, optimizing diagnostic processes in musculoskeletal healthcare. Future research could explore further refinements and real-world implementations to validate these findings and enhance clinical utility, ultimately benefiting patient care and treatment outcomes in orthopedic settings

Naveen Dalal (2019). Diagnosis of Calf Strain using Traditional Fuzzy Rules and Multi Agent System Fuzzy Rules. International Journal on Emerging Technologies, 10(3): 491–496