Analyzing Spatial Patterns of Late-Stage Breast Cancer in Chicago Region: A Modified Scale-Space Clustering Approach

摘要: Breast cancer has ranked highest in incidence Illinois for years. Detection at an early stage helps patients live longer and maintain a better quality of life. Previous research identified two groups potential risk factors late-stage breast diagnosis: spatial including access to healthcare, nonspatial socioeconomic demographic characteristics. Literature suggests that diagnosis behave differently between rural urban areas, needs separate study areas into various geographic settings. This chapter focuses on area six counties Chicago region, examines possible associations several diagnosis. Based the data zip code level, uses modified scale-space clustering (MSSC) method form areas. The MSSC considers both attribute similarity adjacency while minimizing loss information process. Therefore, units defined by are more coherent terms closeness than geopolitical units. For instance, health literature often need urban, suburban or even finer-grained classifications. can be used generate meaningful divisions traditional schemes. analysis results generally consistent across multiple units, demonstrating effectiveness mitigating modifiable areal unit problem (MAUP).