Prosthetic restoration material selection using an integrated Fermatean fuzzy MCDM method
Science progress, cilt.109, sa.3, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 109 Sayı: 3
- Basım Tarihi: 2026
- Doi Numarası: 10.1177/00368504261478359
- Dergi Adı: Science progress
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, EMBASE, INSPEC, MEDLINE, Directory of Open Access Journals, Academic Search Ultimate (EBSCO), Natural Science Collection (ProQuest), Biological Science Database (ProQuest), Biomedical Reference Collection: Corporate Edition (EBSCO), Earth, Atmospheric, & Aquatic Science Collection (ProQuest), Health Research Premium Collection (ProQuest), Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
- Anahtar Kelimeler: clinical decision support, dental prosthetic restoration material selection, Fermatean fuzzy sets, health informatics, patient-centered care
- İstanbul Ticaret Üniversitesi Adresli: Evet
Özet
Selecting an appropriate dental crown material requires the simultaneous consideration of clinical performance, aesthetics, cost, and patient-related expectations. This study aimed to support dentists in selecting the most suitable dental prosthetic restoration material under uncertainty. An integrated Fermatean fuzzy multi-criteria decision-making (MCDM) framework was employed by combining the CRITIC (Criteria Importance Through Intercriteria Correlation) method for weighting and the WASPAS (Weighted Aggregated Sum Product Assessment) method for ranking alternatives. Six restorative material alternatives were evaluated using eleven sub-criteria grouped under three main dimensions: mechanical, visual, and eco-nomic. The criteria were identified through literature review and expert opinion. The findings indicated that clinical longevity was the most important criterion in the evaluation process. Among the six alternatives, the resin nano-ceramic CAD/CAM material achieved the highest overall performance, followed by the lithium disilicate CAD/CAM and zirconia-based ceramic materials. Across the tested λ values and ±20% changes in the three highest-weighted criteria, the ranking order remained unchanged, indicating that the results were stable within the examined sensitivity scenarios, confirming the robustness of the proposed framework. The proposed framework provides a transparent decision-support tool for restorative dentistry and demonstrates the applicability of Fermatean fuzzy MCDM methods to dental material selection.