SAVE THE DATE: August 16-18, 2013
Meaningful Use of Complex Medical Data
The Meaningful Use of Complex Medical Data Symposium (MUCMD) is an interactive annual research meeting to foster the collaboration of computer scientists, data engineers, experts in big data analysis from the machine learning and artificial intelligence communities and health care providers familiar with clinical data and practice.
The purpose of this meeting is to establish a forum for the interaction of computer scientists and those with expertise in machine learning and artificial intelligence to inform the analysis of clinical data by interacting with medical researchers who are subject matter experts. The interaction among these very different groups of researchers is required for health care to truly benefit from the ‘Big Data’ revolution.
Medical data captures complex interrelated phenomena that challenge the analytic abilities of any single expert or group when attempting to learn from complex patient data. Medical data truly manifests the so-called five ‘V’s of big data: volume, velocity, variety, veracity, and value. Because the underlying phenomena are increasingly complex, analyzing large amounts of medical data in a timely fashion requires the ability to combine skills of domain experts from widely separated disciplines, both within (i.e. physicians, nurses, epidemiologists) and outside of health care (i.e. computer scientists, engineers, mathematicians, statisticians).
A major challenge in data analytics in healthcare is that multiple disciplines understand complementary but not necessarily overlapping aspects of the data and must come together with their sophisticated expertise about the intricacies of the problem domain, data analytics, algorithm development and scalability to achieve the promise of ‘big data’ in health care. Currently, these knowledge domains rarely interact and there is no meeting specifically devoted to bringing together experts in advanced data analytics, artificial intelligence and clinical research for the purpose of knowledge discovery from clinical data.