Control of Health-related Risks: Data Science for Proactive Medicine and Healthcare

Abstract

The impact of development of ICT to medical and healthcare services has recently been discussed. In particular, the prevalence of intelligent wearable devices and embedded sensors in daily living environment enable to measure high-quality, multidimensional, and intensive longitudinal biomedical data (ILD) and also access large-scale health-related information. The utility of such data is thought to have a great potential to diagnosis and an early detection of diseases. Therefore, the establishment of a new framework to utilize it, especially a method to extract the useful information associated with diseases, has been focused. Indeed, Horizon2020 in EU incorporated such viewpoints into the projects called in the field of medicine and healthcare. Based on these situations, JST-CRDS also reported on the establishment of proactive health and medical systems for the control of health-related risks. In this talk, we briefly introduce this report and a new data mining framework for biomedical ILD.