An extended Pythagorean fuzzy complex proportional assessment approach with new entropy and score function: Application in pharmacological therapy selection for type 2 diabetes

In the context of medical decision making, the Type 2 Diabetes (T2D) pharmacological therapy selection problem involves several medications that can be stipulated to manage the blood glucose level of patients. The extensive range of hyperglycemia lowering agents with varying outcomes and several side effects makes the decision quite complicated and uncertain. Pythagorean Fuzzy Sets (PFSs) are proven as one of the valuable tools to handle ambiguous and ill-defined problems. This paper introduces an innovative Complex Proportional Assessment (COPRAS) to solve the T2D medication selection problem under the Pythagorean fuzzy environment. In this methodology, a new formula based on entropy measure and score function is introduced to evaluate the unknown criteria weights. To doing so, the new entropy measure and score function are developed under the PFSs context. Further, an illustrative case study of the T2D pharmacological therapy selection problem is taken to express the feasibility and usefulness of the proposed method in real-world decision-making problems. Finally, the obtained result is compared with some existing methods, which confirms the strength and stability of the proposed COPRAS method. (C) 2020 Elsevier B.V. All rights reserved.