New multi-criteria decision-making technique based on neutrosophic axiomatic design

Area of Science:

• Decision Sciences
• Medical Imaging Technology
• Artificial Intelligence

Background:

• Traditional multicriteria decision-making (MCDM) methods struggle with the inherent uncertainty in selecting complex medical equipment.
• Accurate selection of Computed Tomography (CT) devices is crucial for effective medical decision-making and cost efficiency.

Purpose of the Study:

• To extend MCDM methodologies into a neutrosophic environment for improved selection of Computed Tomography (CT) devices.
• To introduce a novel approach that accounts for uncertainty, truth, indeterminacy, and falsity in the evaluation process.

Main Methods:

• Development of a new linguistic scale using single-valued triangular neutrosophic numbers (SVTrN) for evaluating criteria and alternatives.
• Integration of axiomatic design (AD) principles within the neutrosophic MCDM framework.
• Application of the proposed method for selecting appropriate CT devices.

Main Results:

• The proposed neutrosophic MCDM approach effectively simulates human thinking by incorporating degrees of truth, indeterminacy, and falsity.
• Demonstrated superiority over existing methods in handling uncertainty within the CT device selection process.
• The approach offers a simpler yet more comprehensive evaluation compared to traditional MCDM techniques.

Conclusions:

• This research provides a valuable theoretical framework for addressing medical imaging system selection under uncertainty.
• The proposed method can enhance the value of medical imaging and reduce unnecessary costs for healthcare providers and policymakers.
• The study offers practical insights for governments and organizations in designing more effective medical imaging evaluation systems.