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Latest revision as of 13:28, 19 October 2017
Informatics and Data Analytics Core (NS090408)
Specific Aims and Tasks
To expand and broaden the sharing and utilization of research resources and data across centers in order to accelerate the understanding of biological mechanisms for SUDEP, and to develop intervention and prevention measures to reduce SUDEP mortality. The main goal of this Informatics and Data Analytics U01 Core
(IDAC) is to build on the progress already achieved through
MEDCIS infrastructure and to expand and broaden the sharing and utilization of
research resources among our partners. With access to biospecimen materials and
alliances with stakeholder organizations, we continuously boost materials
and data collection.
IDAC promotes and facilitates SUDEP research by expanding an
integrated clinical and translation data resource for epilepsy; provides coordinated
services and support for our members; empowering each investigator with web-based
cohort search interface for data mining and hypothesis generation; data analytics and
statistical support for in-depth analyses of multi-modal data collected in the shared and
expanding CSR Data Repository.
Dr. Jayapandian is a Research Associate in the Medical Informatics Core in the Department of Neurology, CWRU School of Medicine. Her research interests include High Performance Computing on Hadoop, Agile Web Development with Ruby on Rails, Semantic Web - Provenance Metadata Management, Knowledge Representation and Medical Image Processing and Visualization
Dr. Loparo is the Nord Professor and Chair Department of Electrical Engineering and Computer Science, CWRU. His research interests include stability and control of nonlinear and stochastic systems with applications to large-scale electricity systems including generation and transmission and distribution; nonlinear filtering with applications to monitoring, fault detection, diagnosis, prognosis and reconfigurable control; information theory aspects of stochastic and quantized systems with applications to adaptive and dual control and the design of distributed autonomous control systems; the development of advanced signal processing and data analytics for monitoring and tracking of physiological behavior in health and disease.
Dr. Cui is an Assistant Professor in the Department of Computer Science at the
University of Kentucky. She leads the development of Multi-Modality Epilepsy
Data Capture and Integration System (MEDCIS), a powerful and intuitive
ontology-driven query interface for cohort identification over patient data collected
from multiple EMUs. MEDCIS enables clinicians to seamlessly query and create
patient cohorts from multiple participating centers in the CSR project.
Licong's research interests is in information retrieval, information extraction, text
mining, knowledge representation and reasoning, knowledge discovery, ontology
quality assurance, data integration and management, and big data analytics. In
particular, her research goal is to develop computational methods and tools to
solve real-world biomedical and health informatics problems. More details can be
found at her webpage.
Dr. Tao is a Research Assistant Professor in the Division of Biomedical Informatics
at the University of Kentucky. He is the lead developer and project manager for a
variety of ontology-driven data management tools in clinical research settings. He
designed, led, maintains, and continuously refines the Ontology-driven Patient
Information Capture (OPIC) tool, deployed in the EMUs of all CSR clinical sites.
Protocols and Manuals
- Zhang GQ, Siegler T, Saxman P, Sandberg N, Mueller R, Johnson N, Hunscher D, Arabandi S
(2010). VISAGE: A Query Interface for Clinical Research. PMID 21347154.
- Zhang GQ and Bodenreider O (2010). Large-scale, Exhaustive Lattice-based Structural Auditing of
SNOMED CT. AMIA Annual Symposium Proc 2010, pp. 922-926, (Distinguished Paper Award). PMID 21347113.
- Sahoo S, Ogbuji C,, Luo L, Dong X, Cui L, Redline S, Zhang GQ (2011). MiDas: Automatic Extraction
of a Common Domain of Discourse in Sleep Medicine for Multi-center Data Integration. PMID 22195180.
- Tran V, Johnson N, Redline S, Zhang GQ (2011). OnWARD: Ontology-driven Web-based
Framework for Multi-center Studies. PMID 21924379.
- Sahoo S, Zhao M, Luo L, Bozorgi A, Gupta D, Lhatoo S, Zhang GQ (2012). OPIC: Ontology-driven
Patient Information Capturing System for Epilepsy. AMIA Ann. Symposium Proc 2012. PMID 23304354.
- Zhang GQ, Sahoo S, Lhatoo S (2012). From Classification to Epilepsy Ontology and Informatics. PMID 23647220.
- Cui L, Bozorgi A, Lhatoo S, Zhang GQ, Sahoo S (2012). EpiDEA: Extracting Structured Epilepsy and
Seizure Information from Patient Discharge Summaries for Cohort Identification. PMID 23647220.
- Sahoo SS, Lhatoo SD, Gupta DK, Cui L, Zhao M, Jayapadian C, Bozorgi A, Zhang GQ (2013).
Epilepsy and Seizure Ontology: Towards an Epilepsy Informatics Infrastructure for Clinical Research
and Patient Care. PMID 23686934.
- Sahoo SS, Zhang GQ, Lhatoo SD (2013). Epilepsy Informatics and an Ontology-driven Infrastructure
for Large Database Research and Patient Care in Epilepsy. PMID 23647220.
- Jayapandian CP, Chen CH, Bozorgi A, Lhatoo SD, Zhang GQ, Sahoo SS (2013).
Electrophysiological Signal Analysis and Visualization using Cloudwave for Epilepsy Clinical
Research. PMID 23920671.
- Sahoo SS, Jayapandian CP, Chen CH, Bozorgi A, Lhatoo SD, Zhang GQ (2013). Heartbeats in the
Cloud: Distributed Analysis of Electrophysiological “Big Data” using Cloud Computing for Epilepsy
Clinical Research. PMID 24326538.