Using Networks To Understand Medical Data
ISC-CNR and University of Rome La Sapienza
Big Data is impacting and will impact even more most sectors of our lifes. In particular, the healthcare industry could be revolutionized by Big Data analytics since it could improve its operational efficiencies, could help predict disease epidemics and plan responses, enhance the monitoring of clinical trials and in general optimize healthcare spending [1-2].
Starting from examples from orthodontic data [3-5], we will show how applying network analysis helps to visualise, filter and mine complex datasets. We will discuss the general applicability of such approach to medical data and the possibility of implementing a medical doctors' oriented interface for designing and supporting virtual experiments. In such a way, we hope to enlarge and enhance the concept of "data driven medicine", building instruments to let new medical knowledge emerge from Big Data.
 A Look at Challenges and Opportunities of Big Data Analytics in Healthcare, 2013 IEEE International Conference on Big Data, Raghunath Nambiar, Adhiraaj Sethi, Ruchie Bhardwaj, Rajesh Vargheese
 Better Health Care Through Data: How health analytics could contain costs and improve care, By KATHY PRETZ 8 September 2014, http://theinstitute.ieee.org/technology-focus/technology-topic/better-health-care-through-data, http://theinstitute.ieee.org/ns/quarterly_issues/tisep14.pdf
 A network approach to orthodontic diagnosis, Auconi, P., Caldarelli, G., Scala, A., Ierardo, G., & Polimeni, A. Orthodontics & Craniofacial Research,14(4), 189-197 (2011)
 Using Networks To Understand Medical Data: The Case of Class III Malocclusions, Antonio Scala , Pietro Auconi, Marco Scazzocchio, Guido Caldarelli, James A. McNamara, Lorenzo Franchi, PLoS One 7–e44521 (2012)
 Complex networks for data-driven medicine: the case of Class III dentoskeletal disharmony, Antonio Scala , Pietro Auconi, Marco Scazzocchio, Guido Caldarelli, James A. McNamara, Lorenzo Franchi, 2014 New J. Phys. 16 115017
Keywords: Complex Networks, Data Driven Medicine, Interdisciplinary Studies