Cancer Therapy Assessment Accounting for Heterogeneity Using q-Rung Picture Fuzzy Dynamic Aggregation Approach

Due to the fact that there is no symmetry in division of cancer cells, it important consider this asymmetrical behavior. Because heterogeneity during any therapy, not every cell killed only abolished, which sensitive particular treatment chosen. Mathematical models describe these pathways are critical for predicting proliferation The literature on mathematical modeling onset, growth, and metastasis extensive. Both deterministic stochastic factors were used develop mimic development rate cells. We focus cell’s our model so cells generally responsible spreading cancer, called stem can be killed. Aggregation operators (AOs) play an role decision making, especially when several competing factors. A key issue case uncertain data appropriate solutions aggregation process. presented two novel Einstein AOs: q-rung picture fuzzy dynamic weighted averaging (q-RPFDEWA) operator geometric (q-RPFDEWG) operator. Several enticing aspects AOs thoroughly discussed. Furthermore, we provide a method dealing with multi-period decision-making (MPDM) issues by applying optimal solutions. numerical example explain how recommended technique therapy assessment. Authenticity analysis also demonstrate efficacy proposed technique. suggested methodologies applicable real-world multi-stage analysis.