Discrete Mathematical Approaches with Game Theory for Predictive System Modeling

Discrete math assumes an urgent part in clinical applications, yet there is extensive undiscovered capacity in coordinating instructive conversations on discrete math with true instances of numerical demonstrating. In exploration on malignant growth and chemotherapy, to investigate how drug-A prompts obstructions in one sort of cells while passing on one more sort delicate to treatment. Utilizing rigorous mathematical analysis involving various dosage and toxicity functions, our chemotherapy strategy effectively targeted the resistant cells by combining drug A with drug B. A healthcare-specific discrete mathematical model is proposed to optimize the selection of treatments for eliminate tumors. Taking into account a variety of patient-specific variables, visually chart the effective treatment pathways employing the decrease Poisson semi-Lindley distribution model. The game theory provides valuable perspectives on tumor dynamics and treatment strategies for clinical decision-making in chemotherapy. The significance of data-driven, personalized approaches in clinical decision-making is highlighted by the findings, which provide insights into chemotherapy protocols. The transformative impact of data-driven strategies on shaping clinical practices is emphasized in this interdisciplinary framework, which bridges mathematics and healthcare.