From Big Data to Personalized Medicine: An Interactive Process Mining Approach

Abstract

The use of Big Data technologies for inferring new evidences from information collected in patients supposes a great opportunity to support the quality of care in a holistic way. However, the use of machine learning algorithms to create real scientific evidence in order to improve daily protocols in health care has complex barriers to solve. One of the most common barriers is that most algorithms that create scientific evidence from Big Data are considered black boxes by health experts. This produces suspicions over the evidences inferred in physicians. In this paper, a new question driven method for involving health experts in the process by using Process Mining technology is presented.