Qvida+: Development of a Clinical Decision Support System

Abstract

In these last few decades, there has been a significant increase in the average life expectancy due to improved general life conditions as well as to several advances in the medicine field. Contrary to what happened then, people with chronic conditions live more now, and so it's essential to ensure their quality of life. Furthermore, in addition to prolonging their life, another goal of medical treatment is to maintain or increase the quality of life of patients. Health Related Quality of Life (HRQOL) can be defined as the individuals' perception of their own health status (physical, functional, emotional and social) and the impact of their condition or treatment in their daily life (job, family, friends). The QVida+ project, based on recent scientific and technological advances in the HRQOL fields and mobile devices, intends to create an innovative paradigm when it comes to the assessment and application of HRQOL. The following step to this project, and the aim of the current dissertation would be the development of a clinical support system that would gather all the data collected in previous steps of this project such as biometric data (e.g., sleep, heart rate variability) and physical activity( e.g., number of daily steps) collected through smartbands, responses to self-report questionnaires and clinical data from cancer patients and provide health care professionals with more and better information about their patients. This system, with the help of machine learning (ML) techniques, would focus particularly on patients' evolution regarding their health status and HRQOL, and consequently assist health care professionals on future decisions with greater quantity and quality of information.