Eliot Siegel
Practical Applications Of Big Data and Big Analytics For Decision Support in Medicine and Diagnostic Imaging

Wednesday, March 25, 2015
Building 3 Auditorium - 11:00 AM
(Coffee and cookies at 10:30 AM)

"BIG DATA" is currently one of the hottest topics in medicine from a research and clinical perspective. However, it's impossible to get any consensus on its definition. IBM and others have defined it in terms of the four V's, volume, velocity, variety, and, particularly relevant to healthcare, veracity. Whichever definition that we may use when thinking of "Big Data", medicine and in specific, diagnostic imaging clearly generates vast amounts of it. The volume and complexity of medical information in healthcare has doubled every five years with 80% or more of that data unstructured.

One of the major challenges with medical imaging in particular is the difficulty of discovery of imaging information in the electronic medical record and from clinical trial data. Our imaging reports are, almost without exception, unstructured and our medical images are rarely tagged in such a way as to be discoverable or useful to data mining efforts. This must change if medical imaging is to play a substantial role in this era of big data, medical guidelines, decision support and personalized medicine.

The goals of this presentation include defining "Big Data" and issues such as archival of clinical images and other data and metadata, exploring the current role and applications of big data in medicine and diagnostic imaging with an emphasis on clinical applications and speculating about the potential and future applications of Big Data to help in visualization of images and data, and diagnosis and treatment. Practical applications for decision support and screening will be presented.

Dr. Eliot Siegel is Professor and Vice Chair of Research Information Systems at the University of Maryland School of Medicine, Department of Diagnostic Radiology, as well as Chief of Radiology and Nuclear Medicine for the Veterans Affairs Maryland Healthcare System, both in Baltimore, MD. He is the director of the Maryland Imaging Research Technologies Laboratory. He has adjunct appointments as Professor of Bioengineering at the University of Maryland College Park and as Professor of Computer Science at the University of Maryland Baltimore County campus.

Dr. Siegel was recently appointed to serve on the National Library of Medicine's Board of Scientific Counselors. Under his guidance, the VA Maryland Healthcare System became the first filmless healthcare enterprise in the United States. He has written over 300 articles and book chapters about PACS (Picture Archiving and Communication Systems) and digital imaging, and has edited six books on the topic, including Filmless Radiology and Security Issues in the Digital Medical Enterprise. He has made more than 1,000 presentations throughout the world on a broad range of topics involving the use of computers in medicine.

Dr. Siegel has won numerous teaching awards at the University of Maryland including medical school mentor of the year. He has been named as overall Radiology Researcher of the Year by his peers and separately as Educator of the year. Dr. Siegel has also been selected by the editorial board of Medical Imaging as one of the top radiologists in the US on multiple occasions. He was overall symposium chairman for the Society of Photo-optical and Industrial Engineers (SPIE) Medical Imaging Meeting for three years, served as chair of Publications for the Society of Computer Applications in Radiology (SIIM) and has been honored as a fellow in that organization and has served multiple terms on the board of directors for SIIM. He has served as chairman of the RSNA's Medical Imaging Resource Committee. Dr. Siegel also worked with the IBM "Jeopardy" team to help "educate" the "Dr. Watson" software in the field of medicine. His areas of interest and responsibility at both the local and national levels include digital imaging and PACS, telemedicine, the electronic medical record, and informatics and artificial intelligence in medicine.

IS&T Colloquium Committee Host: Jacqueline LeMoigne

Sign language interpreter upon request: 301-286-7040