ArticleACS omega2026
Evaluation of Wound-Healing Potential of Plant Extracts via Picture Fuzzy Multi-Attribute Decision-Making.
Article in ACS omega, 2026. 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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Authors and funding
2 authors.
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Abstract
The rising number of chronic wounds across the world makes the creation of efficient, environmentally friendly and cost-effective wound healing biopolymers an urgent need in the sphere of biopharmaceuticals. However, the selection of the most appropriate candidate from many natural plant extracts with complex and heterogeneous phytochemical composition is a difficult task of multiattribute decision-making (MADM) because of uncertainties, hesitations in expert judgments, and incomplete experimental data. A new hybrid approach of MADM with the use of picture fuzzy sets (PFS) is suggested in this paper as a realistic model of human logical judgment with membership degrees that cover positive, negative, neutral, and refusal aspects. Within the context of this study, the PiF-DEMATEL method is used to estimate causal relationships between eight attributes related to tissue repairing performance and attribute weights, while the PiF-PIV method that has been elaborated for the first time in the literature in this study is proposed as a tool for ranking ten different plant extracts. According to the attribute analysis, the "anti-inflammatory effect" (0.150) and "cell regeneration" (0.147) attributes, belonging to the group of physiological response attributes, were shown to have the highest importance, whereas the "Phytochemical content" (0.145) criterion was revealed to be the most dominating causative factor controlling the underlying biochemical engine.
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Registered trials
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