Data analytics oriented to personalized medicine. Use cases

Friday, August 4, 2017

In recent times, data analysis discipline is considerably increasing its capacity of action in several fields and sectors of society. The improvement of technology, together with a greater ability to acquire, transmit and store information, results in a wealth of information and data available (Big Data). With a view to discover the implicit knowledge from data, it is necessary the use of leading data analytics techniques, such as Machine Learning techniques.

ICCB 2017

The application of data mining techniques in Medicine offers and enormous potential for many medical areas, like for example genomics, clinical trials, epidemiology or tele-assistance. In this sense, we aim at creating value, by providing medical services that are more effective, as well as allowing both the personalization of the service itself and the optimization of available resources. Personalized medicine increases the relationship among doctors and patients, which leads to the active participation of all the agents involved. Moreover, the analysis of data applied to health eases the design of new treatments; leads to more effective clinical decision making; and provides more efficient prevention approaches.

The “Wellbeing and active aging” and “Intelligent Data Analysis” specialization areas at CTIC Technology Centre are committed to the research and development of solutions, leading to possible breakthroughs in this field. In particular, our team of experts and researchers is currently working on the following application fields:

  • Analysis of the biomechanical factors that influence the human gait, through the study of the accelerations. The objective is to evaluate the quality of patient’s gait after a surgical intervention and to analyze the risk of falls in elderly people. This analysis also allows the design and planning of personalized rehabilitation treatment plans and routines.
  • Active surveillance of patients with bipolar disorder, through the analysis of their physical activity, using accelerometer-based solutions. Our objective is to predict and anticipate disease progress, which will allow adjusting the treatment and hence anticipating or delaying appointments with the specialist.
  • Study of the main chronic diseases in order to identify and monitor the medical and social variables that directly influence them. This will facilitate patients’ segmentation or stratification and allow for the deployment of action plans for those in whom the risk of worsening is greater.

To sum up, the application of analytical techniques in the description, prediction and prescription within the health sector, contributes to improve the medical care system for people and therefore, their physical and social well-being.