An Efficient Framework for Drug Product Selection – DPS according to Neutrosophic BWM, MABAC and PROMETHEE II Methods

Abstract

Developments of systems in healthcare and medical sector have greatly influenced the way we shape our life. Several successful techniques, algorithms and systems have been proposed to solve small version of the change state of each drug according to specific patient. Traditional algorithms and techniques are faced by many difficulties such as (Large Scale, Continuous change of both drug set and patient state, and lack of information). In this study, we propose a methodology for Drug Products Selection - DPS according to every patient individually based on a real data set of US drug bank. A Best Worst Method (BWM), MultiAttributive Border Approximation Area Comparison (MABAC). And Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II) are suggested as a systematic procedure for assessing drug products under the canopy of Neutrosophic theory. Bipolar Neutrosophic Linguistic Numbers (BNLNs) handles the ambiguity, and uncertainty by bipolar Neutrosophic scale, BWM calculates the significance weights of assessment criteria, MABAC as an accurate method assesses drug products, and PROMETHEE II presents effectiveness arrangements of the possible alternatives. A case of 7 real drug products of a real patient against 7 criteria are assessed by 3 doctors to measure the accuracy of the suggested methodology.