A Neutrosophic Cubic Hesitant Fuzzy Decision Support System, Application in the Diagnosis and Grading of Prostate Cancer

According to available estimates with WHO, cancers are the sixth leading cause of global human morbidity and mortality. Prostate Cancer is fifth-ranked most lethal among various cancers, hence it warrants serious, dedicated research for improving its early detection. The employed methodologies such as prostate-specific antigen test, Gleason Score, T2 Staging lack precision accuracy in conditions where information scarring, vague uncertain. Consequently, present study, innovative use neutrosophic cubic fuzzy sets (NCFS) improve prostate cancer detection situations basic vague, imprecise, Specific critical similarity measures defined using NCFS methodology evaluation cancer. This found reasonably better compared existing benchmark methods grading