Smart Network to Monitor Breast Cancer Patient Based on Network Arrangement and Fuzzy Hierarchy Analysis

Javad Nouri Pour ¹ ( Department of Mechanics, Electrical Power and Computer- Science and Research Branch, Islamic Azad University, Tehran, Iran )
Mohammad Ali Pourmina ² ( Department of Mechanics, Electrical Power and Computer- Science and Research Branch, Islamic Azad University, Tehran, Iran )
Mohamed Naser Moghadasi ³ ( Department of Mechanics, Electrical Power and Computer- Science and Research Branch, Islamic Azad University, Tehran, Iran )
Behbod Ghalamkari ⁴ ( Department of Mechanics, Electrical Power and Computer- Science and Research Branch, Islamic Azad University, Tehran, Iran )

Submited date : 2022-12-09 Accepted date : 2023-04-05

Keywords: fuzzy hierarchical analysis, Nodes, breast tumor, connection weight, network capability arrange‌me‌nt,

Abstract :

In this article, a smart network is proposed to monitor a patient with breast cancer. Increasing the speed of the patient monitoring network depends on our observation, thinking and understanding of the patient. Various factors of the network make us more aware of the disease. has it. The cycle of controlling and monitoring the patient includes observation, orientation, decision and action, this cycle is a set of consecutive actions, which changes with the change of network arrangement, orientation, decision and action. In this article, we design the structure of the smart network according to the weight of the nodes, the communication paths in such a way that the cycle of control and monitoring (analysis, decision and action) performs well. We model the control and monitoring cycle with the proposed method of fuzzy hierarchical analysis process (FAHP). This model adjusts the decision-making criteria by recognizing the identification priorities in such a way that the speed of network detection increases with the least time. It is also a suitable tool for modeling the monitoring cycle and the results of the smart network. The simulation results show that this network has the necessary intelligence to assess the patient's condition in adverse conditions, has the power to continuously analyze and evaluate the patient, and also has the power to make timely decisions in different situations. These results show that according to the network arrangement and fuzzy hierarchical analysis, the speed rate of the network has improved by 10% compared to other networks.

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