Classification of Body Composition and Activity Patterns by Data Mining on Healthcare 

Data Healthcare data is rapidly increasing as healthcare smart devices are developed. However, statistical analysis of healthcare big data is difficult due to heterogeneity in data quality and missing data. For such data, data mining methods such as clustering and dimension reduction may be useful as their preliminary analysis. In this talk, two illustrative applications are provided; one is a principal component analysis of body composition data and the other is a latent topic analysis of hourly step-count dataset recorded by physical activity monitors. From those analyses, an index of hidden obesity and some daily and weekly patterns in ambulatory activities are proposed.