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WSA Webinar - Big data: a game-changer to advance stroke care in the digital era
Large, frequently updated sets of data generated in the “real world”, often from different sources, can lead to breakthroughs that effectively impact clinical practice. This webinar will provide WSO members with key information about how to manage data collected in daily clinical practice or in research studies, in order to build or contribute to Big Data initiatives able to answer pressing questions in stroke care. One talk will revise basic concepts, one will focus on an example of an ongoing Big Data project in stroke rehabilitation research, and one will address guidelines to ensure quality of data collection, analysis, storage and sharing. This educational activity will prepare the audience to create or participate in networks or novel pragmatic trials in large stroke cohorts in different regions of the globe. This webinar will address tools to develop innovative therapies in general but also to promote research in acute care, prevention, diagnosis and rehabilitation.

- Big Data in stroke (Benjamim Bray)
- Data science and Open Science: impact on reproducibility in stroke rehabilitation research (Sook-Lei Liew)
- Data science: dos and don'ts (Edson Amaro Jr)
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Speakers

Sook-Lei Liew
Associate Professor and Director @Neural Plasticity and Neurorehabilitation Laboratory at the University of Southern California
Sook-Lei Liew is an Associate Professor and Director of the Neural Plasticity and Neurorehabilitation Laboratory at the University of Southern California. She has joint appointments in the divisions of Occupational Science and Occupational Therapy, Biokinesiology and Physical Therapy, Biomedical Engineering, Neuroscience, and Neurology, and is a member of the USC Stevens Neuroimaging and Informatics Institute. She is the Chair of the ENIGMA Stroke Recovery Working Group, which aims to aggregate and analyze high-resolution brain imaging and behavioral outcomes in individuals after stroke from thousands of patients collected across more than 50 research cohorts from 10 countries worldwide. She also is a co-director and co-founder of the USC SMART-VR (SensoriMotor Assessment and Rehabilitation Training) Center (smartvr.usc.edu).
Edson Amaro Jr.
neuroradiologist and Head Big Data Analytics @Albert Einstein Hospital
Prof. Dr. Edson Amaro Jr is a neuroradiologist and Head Big Data Analytics at Albert Einstein Hospital. He graduated in medicine with a PhD in neuroimaging at University of São Paulo, and finished postdoctoral degree from the Institute of Psychiatry, King's College London. He was head of the Albert Einstein Hospital Brain Institute from 2008 to 2012. He is responsible for clinical (predictive and prescriptive) and management (cost / effectiveness and resource optimization) applications in projects at Einstein and in partnership with Government helping to advance the health public system. He is the author / co-author of more than 240 scientific articles peer reviewed scientific journals.
Ben Bray
Medical doctor, Epidemiologist, Principal in the Health Analytics team @Lane Clark and Peacock and King's College London
Ben is a medical doctor and epidemiologist with a clinical background in nephrology and public health medicine, and is Principal in the Health Analytics team at Lane Clark and Peacock, and He has more than 10 years’ experience designing and carrying out studies using real world health data such as electronic medical records, registries and biobanks. He has published extensively in stroke epidemiology and health services research, and previously was Research Director of the Sentinel Stroke National Audit Programme (SSNAP), the national quality registry for stroke care in England, Wales and Northern Ireland. His previous roles have included Clinical Lead (Stroke) for the National Cardiovascular Intelligence Network of Public Health England, and Clinical Advisor to NHS England and NHS Kidney Care. He is an Honorary Senior Clinical Lecturer at King’s College London, where he works on research into machine learning analytics using large health databases.