Title :
Clustering of Sun exposure measurements
Author :
Szymkowiak-Have, A. ; Larsen, J. ; Hansen, L.K. ; Philipsen, P.A. ; Thieden, E. ; Wulf, H.C.
Author_Institution :
Informatics & Math. Modelling, Tech. Univ. Denmark, Lyngby, Denmark
Abstract :
In a medically motivated Sun-exposure study, questionnaires concerning Sun-habits were collected from a number of subjects together with UV radiation measurements. This paper focuses on identifying clusters in the heterogeneous set of data for the purpose of understanding possible relations between Sun-habits exposure and eventually assessing the risk of skin cancer. A general probabilistic framework originally developed for text and Web mining is demonstrated to be useful for clustering of behavioral data. The framework combines principal component subspace projection with probabilistic clustering based on the generalizable Gaussian mixture model.
Keywords :
Gaussian processes; Sun; cancer; medical signal processing; pattern clustering; principal component analysis; radiation detection; Sun exposure measurements clustering; Sun-habits; UV radiation measurements; behavioral data clustering; generalizable Gaussian mixture model; heterogeneous data set; latent semantic indexing; medical records; multiple data types; principal component subspace projection; probabilistic clustering; questionnaires; received sun radiation; skin cancer risk; Biomedical imaging; Data mining; Electronic mail; Hospitals; Mathematical model; Matrix decomposition; Sampling methods; Skin cancer; Sun; Training data;
Conference_Titel :
Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on
Print_ISBN :
0-7803-7616-1
DOI :
10.1109/NNSP.2002.1030090