Disease mapping aims to estimate the spatial pattern in disease risk across an area, identifying units which have elevated disease risk. Existing methods use Bayesian hierarchical models with spatially smooth conditional autoregressive priors to estimate risk, but these methods are unable to identify the geographical extent of spatially contiguous high-risk clusters of areal units. Our proposed...

These studies examine the relationship between the analytic basis underlying the hierarchies produced by the Model of Hierarchical Complexity and the probabilistic Rasch scales that places both participants and problems along a single hierarchically ordered dimension. A Rasch analysis was performed on data from the balance-beam task series. This yielded scaled stage of performance for each of t...

Hierarchical clustering is one of the most powerful solutions to the problem of clustering, on the grounds that it performs a multi scale organization of the data. In recent years, research on hierarchical clustering methods has attracted considerable interest due to the demanding modern application domains. We present a novel divisive hierarchical clustering framework called Hierarchical Stoch...

L. Kohlberg (1969) argued that his moral stages captured a developmental sequence specific to the moral domain. To explore that contention, the author compared stage assignments obtained with the Standard Issue Scoring System (A. Colby & L. Kohlberg, 1987a, 1987b) and those obtained with a generalized content-independent stage-scoring system called the Hierarchical Complexity Scoring System (T....

PURPOSE Classification based on a combination of molecular and pathologic predictors had never been done using hierarchical cluster analysis. For this purpose, we identified prognostic classification based on molecular predictors, pathologic and molecular predictors, and compared their respective prognostic efficacy together with that of tumor-node-metastasis (TNM) stage. Moreover, we investiga...

Many image processing tasks exist and segmentation is one of them. We are focused on the mean-shift segmentation method. Our goal is to improve its speed and reduce the over-segmentation problem that occurs with small spatial bandwidths. We propose new mean-shift method called Hierarchical Layered Mean Shift. It uses hierarchical preprocessing stage and stacking hierarchical segmentation output...

Introduction Breast cancer is the second cause of mortality among women. Early detection of it can enhance the chance of survival. Screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. Computer-aided diagnosis can help physicians make a more accurate diagnosis. Materials and Methods Regarding the importance of separating normal and abnorm...