Trends and Developments in Fuzzy Logic for Medical Diagnosis: A Bibliometric Analysis
Baltic Journal of Modern Computing, cilt.13, sa.4, ss.806-833, 2025 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 13 Sayı: 4
- Basım Tarihi: 2025
- Doi Numarası: 10.22364/bjmc.2025.13.4.04
- Dergi Adı: Baltic Journal of Modern Computing
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
- Sayfa Sayıları: ss.806-833
- Anahtar Kelimeler: artificial intelligence in healthcare, bibliometric mapping, Clinical decision support systems, research trends, uncertainty modeling
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Ankara Üniversitesi Adresli: Evet
Özet
The complexity and uncertainty inherent in medical diagnosis pose significant challenges for accurate and timely decision-making. To address these challenges, advanced technologies such as clinical decision support systems have gained prominence. Integrating fuzzy logic (FL) into these systems offers a practical solution for managing uncertainty, as it provides a more flexible framework than traditional binary (on-off, zero-one) approaches. In particular, FL has contributed to improved diagnostic accuracy, the handling of uncertainty and vagueness in patient-reported symptoms, and the support of decision-making when data is incomplete or ambiguous. This study presents a bibliometric analysis of the leading research trends in this field, offering insights into the evolution and impact of FL in medical diagnosis. By facilitating the representation of nuanced degrees of clinical parameters such as pain intensity or fever severity, FL enables the modeling of complex disease patterns, the development of predictive analytical models, and the construction of intelligent healthcare systems. This capability enhances diagnostic precision, supports early detection, and extends the applicability of decision support tools to complex and uncertain clinical scenarios. At the time of conducting this bibliometric analysis, searches in Scopus databases revealed no prior bibliometric studies focused on the application of FL in medical diagnosis.