Study on Missing People Search Method on Follow-up of Breast Cancer Cohort

In medical cohort studies, the frequent movement of population leads to incomplete data, which greatly interferes with research results. This article refers to such problems as the search for missing people (SMP) problem. Based on the idea of social network information propagation, we propose a propagation contribution-driven missing people search mechanism (MPSM). MPSM exploits social networks to gather information from users and then dynamically evaluates the ability of users to help find missing people Using the two most complete and widely used data sets of social networks Facebook and Twitter, MPSM method was compared with seven common information transmission models (Independent Cascade method, Linear Threshold method, Random Process method etc.), and the success rate, propagation scale, and propagation cost were taken into comprehensive account to prove the validity of MPSM model. Follow-up data from the breast cancer cohort study were then used for pre-sampling experiments, and the results showed that the MPSM success rate reached 58.9%(95%CI 45.0%~71.9%). To sum up, MPSM has important application value in SMP.