A Cubic Bipolar Complex Neutrosophic Numbers (CBCNN) Model for Massive Heart Attack Risk Assessment

Abstract

The prediction of Heart Attact remains challenging due to the conflicting, incomplete, and time-varying nature of clinical evidence. This paper proposes a novel decision-support framework based on Cubic Bipolar Complex Neutrosophic Numbers (CBCNN), which jointly captures truth, indeterminacy, and falsity of risk evidence (neutrosophic), separates risk-elevating from risk-reducing factors (bipolar), represents both interval and point valued observations over a monitoring window (cubic), and encodes trend urgency through a phase component (complex). A Cubic Bipolar Complex Neutrosophic Number framework is proposed to model the uncertainty associated with two key heart attack symptoms (chest pain and shortness of breath) for the classification of two heart attack types partial or complete blockage of artery else silent attack, enabling robust medical decision making under ambiguity.