On November 20, 2015, IEEE EMBS Atlanta and IEEE SPS Atlanta jointly hosted Prof. Ervin Sejdić speaking on the subject of "From big data to functional outcomes: Can we use large data sets to understand changes in swallowing, gait and cerebral functions?"
A biomarker is defined as a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In recent years, there has been growing emphasis on the utility of molecular biomarkers, usually to identify molecules whose detection indicates a particular disease state. Although, molecular biomarkers are useful under certain conditions, complementary approaches to probe other characteristics of a living system may provide crucial information when molecular biomarkers are difficult to identify. In this talk, he will present his efforts to develop dynamical biomarkers that can characterize temporal and spatial signatures (i.e., the unique patterns of moment-to-moment changes of physiologic variables under normal or pathologic conditions) and their relationship to other variables. Specifically, he will elaborate my efforts to develop computational biomarkers for detecting swallowing difficulties, gait changes and changes in cerebral blood flow. These computational biomarkers are obtained by mining large data sets in order to characterize changes in the considered functional outcomes under various conditions.
Dr. Ervin Sejdić received B.E.Sc. and Ph.D. degrees in electrical engineering from the University of Western Ontario, London, Ontario, Canada in 2002 and 2008, respectively. From 2008 to 2010, he was a postdoctoral fellow at the University of Toronto with a cross-appointment at Bloorview Kids Rehab, Canada's largest children's rehabilitation teaching hospital. From 2010 until 2011, he was a research fellow at Harvard Medical School with a cross-appointment at Beth Israel Deaconess Medical Center. From his earliest exposure to research, he has been eager to contribute to the advancement of scientific knowledge through carefully executed experiments and groundbreaking published work. This has resulted in co-authoring over 80 publications in the last 5 years. Dr. Sejdić's passion for discovery and innovation drives his constant endeavors to connect advances in engineering to society's most challenging problems. Hence, his research interests include biomedical signal processing, vascular aging, gait analysis, swallowing difficulties, advanced information systems in medicine, rehabilitation engineering, assistive technologies and anticipatory medical devices.
The IEEE EMBS and IEEE SPS are grateful to Dr. Sejdić for giving this lecture.
On April 22, 2015, IEEE EMBS Atlanta hosted a distinguished lecture by May D. Wang on "Biomedical Big Data Analytics for Patient-Centric and Outcome-Driven Health Care."
Rapid advancements in biotechnologies such as -omic (genomics, proteomics, metabolomics, lipidomics etc.), next generation sequencing, bio-nanotechnologies, molecular imaging, and mobile sensors, etc. accelerate the data explosion in biomedicine and health wellness. Multiple nations around the world have been seeking novel effective ways to make sense of "big data" for evidence-based, outcome-driven, and affordable 5P (Patient-centric, Predictive, Preventive, Personalized, and Precise) healthcare. Dr. May Wang conducts multi-modal and multi-scale (i.e., molecular, cellular, whole body, individual, and population) biomedical data analytics research for discovery, development, and delivery, including translational bioinformatics in biomarker discovery for personalized care; imaging informatics in histopathology for clinical diagnosis decision support; bionanoinformatics for minimally-invasive image-guided surgery; critical care informatics in ICU for real-time evidence-based decision making; and chronic care informatics for patient-centric health management.
In this talk, first, Dr. Wang will highlight major challenges in biomedical and health informatics pipeline consisting of data quality control, information feature extraction, advanced knowledge modeling, decision making, and proper action taking through feedback. Second, she will present informatics methodological research in (i) data integrity and integration; (ii) case-based reasoning for individualized care; and (iii) streaming data analytics for real-time decision support using a few mobile health case studies (e.g., Sickle Cell Disease, asthma, pain management, rehabilitation, diabetes, etc.). Last, there is big shortage of data scientists and engineers who are capable of handling Big Data. In addition, there is an urgent need to educate healthcare stakeholders (i.e., patients, physicians, payers, and hospitals) on how to tackle these grant challenges. Dr. Wang will discuss efforts such as patient-centric educational intervention, community-based crowd sourcing, and Biomedical Data Analytics MOOC development.
Dr. Wang's research has been supported by NIH, NSF, Georgia Research Alliance, Georgia Cancer Coalition, Emory-Georgia Tech Cancer Nanotechnology Center, Children's Health Care of Atlanta, Atlanta Clinical and Translational Science Institute, and industrial partners such as Microsoft Research and HP.
May D. Wang, Ph.D. is an Associate Professor in the Joint Department of Biomedical Engineering, School of Electrical and Computer Engineering, Winship Institute, Institute for Bioengineering and Biosciences, and Institute for People and Technology at Georgia Institute of Technology and Emory University, USA. Dr. Wang is a Kavli Fellow, a Georgia Research Alliance Distinguished Cancer Scholar, a newly elected fellow of The American Institute for Biological and Medical Engineering (AIMBE).
Prof. Wang's research is in Biomedical Big Data analytics with a focus on Biomedical and Health Informatics (BHI) for Personalized and Predictive Health. Her research includes high throughput NGS and -omic data mining to identify clinical biomarkers, bionanoinformatics, pathological imaging informatics to assist clinical diagnosis, critical and chronic care health informatics for evidence-based decision making, and predictive systems modeling to improve health outcome. Prof. Wang published 160+ peer-reviewed articles in BHI. She is the corresponding/co-corresponding author for articles published in Journal of American Medical Informatics Association, Journal of Biomedical and Health Informatics, Briefings in Bioinformatics, BMC Bioinformatics, Journal of Pathology Informatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Proceedings of The IEEE, IEEE Transactions on Information Technology in Biomedicine, BMC Medical Imaging, Annals of BME, Trends in Biotechnology, Nature Protocols, Proceedings of National Academy of Sciences, Annual Review of Medicine, Circulation Genetics, and Nanomedicine etc. She has led RNA-data analysis investigation within FDA-led Sequencing Consortium (SEQC). Dr. Wang has devoted to training of young generation of data scientists and engineers, and she received Georgia Tech's Outstanding Faculty Mentor for Undergraduate Research Award in 2005.
Currently, Prof. Wang serves as the Senior Editor for IEEE Journal of Biomedical and Health Informatics (J-BHI), an Associate Editor for IEEE Transactions on Biomedical Engineering (TBME), and an Emerging Area Editor for Proceedings of National Academy of Science (PNAS). She also serves as IEEE EMBS Biomedical and Health Informatics Technical Committee Chair. She is an IEEE-EMBS 2014-2015 Distinguished Lecturer, and an EMBS Administrative Committee Officer representing North America.
Dr. Wang is the Biocomputing and Bioinformatics Core Director in Emory-Georgia-Tech Cancer Nanotechnology Center, a Co-Director of Georgia-Tech Center of Bio-Imaging Mass Spectrometry, and a Co-Director of Biomedical Informatics Program of Georgia Tech in Atlanta Clinical and Translational Science Institute.
The IEEE EMB Society is grateful to Dr. Wang for giving this distinguished lecture.
Last updated April 6, 2022.
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