Managed by the NSF CAKE: National Science Foundation Industry/University Cooperative Research Center for Advanced Knowledge Enablement at Florida International, Florida Atlantic, and Dubna International Universities
Steering Committee Chair: Joyce Elam
Director: Naphtali Rishe
The Health Information Technology Initiative managed by the FIU-FAU NSF Center provides expertise Data Extraction, Clinical Messaging, Disease Registries, Bio-surveillance, Patient Monitoring, and Patient Communication. The Center provides infrastructure to develop clinical data management applications and collaboration tools that aid in the collection, storage, management and analysis of data from multiple sites to support the clinical, biomedical and translational research activities of affiliated academic institutions and Industry Members of the FIU NSF CAKE Center. Please see our recent publications on HIT, including NSF post-workshop book.
Geospatial Public Health:
Please see a powerpoint on Geospatial-temporal analytics of correlation of environmental factors and incidence of disease. This research thrust, led by Dr. Naphtali Rishe of Florida International University's High Performance Database Research Center, focuses on the development of innovative tools and concept demonstrations that show the solvability of Big Data problems involving geospatial data correlated with publically available medical data. We bring the Big Data approach to geospatial epidemiology, a field of study focused on describing and analyzing geographic variations of disease spread, considering demographic, environmental, behavioral, socioeconomic, genetic, and infectious risk factors. Our work in this area assists the development of the related field of personalized medicine by correlating clinical, genetic, environmental, demographic, and other background geospatial data. Our TerraFly GeoCloud system combines several diverse technologies and components in order to analyze and visualize geospatial data. In this system, a user can upload a spatial dataset and display it using the TerraFly Map API. Datasets can be subsequently analyzed using various functions, such as Kriging, a geo-statistical estimator for unobserved locations, and Spatial Clustering, which involves the grouping of closely related spatial objects. Various analysis functions related to spatial epidemiology have been integrated into TerraFly GeoCloud. Analysis functions can be used by selecting the appropriate dataset and function in the interface menu, along with the variables to be analyzed. TerraFly GeoCloud then processes the data and returns a result that can be visualized on the TerraFly Map or on a chart. Results displayed on the map include a legend, which identifies certain range values by color. Certain visualizations are interactive, allowing additional information to be displayed. Our Spatial Epidemiology System provides four kinds of API algorithms for data analysis and results visualization, based on the TerraFly GeoCloud System: (1) disease mapping (mortality/morbidity map, SMR map); (2) disease cluster determination (spatial cluster, HotSpot analysis tool, cluster and outlier analysis); (3) geographic distribution measurement (mean central, median central, standard distance, distributional trends); and (4) regression (linear regression, spatial auto-regression). Furthermore, the system is interfaced with our Health Informatics projects. Researchers in this thrust work with the Center's other thrusts to obtain datasets containing a large number of patient records including demographic, clinical and genomic data. The demographic data is analyzed and processed to render approximate geolocation. A high-performance query interface is created to co-query records on the basis of geographic, clinical, and genomic attributes. Interactive data maps and heat maps will be created. The datasets will be minable for derivation of knowledge. Live demonstrations of a publically deliverable view of results will be posted on the Web. We work on tools and methodologies that will assist in operational and analytical health informatics. The TerraFly Geospatial Analytics System (http://terrafly.com) demonstrates correlation of location to environment-related disorders, enabling clinicians to more readily identify macro-environmental exposure events that may alter an individual.s health. It will also enable applications in targeted vaccine and disease management, including disease surveillance, vaccine evaluation and follow-up, intelligent management of emerging diseases, cross-analysis of locations of patients and health providers with demographic and economic factors, personalized medicine, and other geospatial and data-intensive applications. This thrust is led by Dr. Naphtali Rishe, the inaugural Outstanding Professor of FIU. Dr. Rishe's research at FIU was funded by agencies at over $55 million, including over $20M from NSF, particularly for Geospatial Data Management (TerraFly) and Personalized Medicine Informatics.
Nationwide Health Information Network (NHIN):
FIU and the NSF-CAKE hosted the Spring 2010 CONNECT Code-a-Thon organized by the Federal Health Architecture (FHA) in the Office of National Coordinator for Health Information Technology (ONCHIT) in the Department of Health and Human Services (HHS). The event took place April 28th-29th, 2010 in Miami, FL, and was opened by FIU President Mark Rosenberg.
Naphtali D. Rishe, 305-348-1706
University Park, FIU ECS-243, Miami, FL 33199; FAX: (305) 348-1707