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Prosthetic restoration material selection using an integrated Fermatean fuzzy MCDM method.
Article in Science progress. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.