13. From telemedicine to modeling and proactive medicine

Abstract

Contemporary healthcare delivers vast amounts of data. Telemedical systems contribute considerably to this, broadening the spectrum of available information greatly to include: -general medical and social profiles -history of previous therapies -laboratory and imaging examination results -records of everyday activities of patients and prescribed rehabilitation -records of food calories and times of meals -basic body parameters such as blood pressure, heart rate, body weight, temperature, blood glucose level, etc. -records of drug intakeThe sensing and monitoring of our life activity is going to be pervasive [1]. It will be a source of very valuable information which may considerably improve healthcare operation leading to personalized and proactive medicine, currently perceived as a very promising research area. At the same time demand for healthcare will become more and more widespread due to commonly observed trends: -better living conditions (including medical care) and civilization progress mean that people live longer than before. An ageing population is, however, at greater risk of cognitive impairment and frailty -chronic diseases like obesity and diabetes affect a considerable percentage of the population in highly developed countries -intensive and successful promotion of a healthy lifestyle and awareness of the importance of self-management of health and diseases Efficient utilization of this information requires employing advanced ICT technologies such as big data processing, machine learning, cognitive computing, predictive analytics etc. One of the interesting areas of medical data processing is modeling of selected aspects of human body behavior, supporting medical diagnoses and proactive treatment. This chapter presents how existing telemedical systems may contribute to this vision of future medicine. In Section 13.2 the traditional model of healthcare supported