Title :
MOOC for Medical Big Data Research: An Important Role in Hypertension Big Data Research
Author :
Wang Xinyan ; Tian Liyuan ; Xu Bo ; Wang Xueliang ; Wu Wenjun
Author_Institution :
Special Diagnostics Dept., Air Force Gen. Hosp., Beijing, China
fDate :
March 30 2015-April 2 2015
Abstract :
Due to limited technical and social resources, many physician practices fall short on accurate blood pressure measurement to carry out large-scale hypertension research projects. The accuracy and standard of data acquisition are very important when data sources are diverse in medical big data research. This paper proposes Massive Online Open Course (MOOC) is appropriate approach to teach volunteers necessary knowledge and skills of blood pressure measurement for hypertension research. It introduces a new citizen science "paradigm" to support big data research such as hypertension. MOOC is a new type online course that provides a combination of short video lectures, frequent comprehension quizzes and active participation in discussion forum. The well-trained data collectors by MOOC will be granted to collect and publish data of hypertension research. The process of medical big data research based on MOOC was introduced.
Keywords :
Big Data; biomedical education; blood pressure measurement; computer aided instruction; data acquisition; educational courses; medical computing; medical information systems; research and development; MOOC; blood pressure measurement; citizen science paradigm; comprehension quizzes; data acquisition; data collector; data source; discussion forum; hypertension big data research; large-scale hypertension research project; massive online open course; medical big data research; online course; physician; video lecture; Big data; Biomedical monitoring; Blood pressure; Hypertension; Pressure measurement; Standards; Massive Online Open Course; hypertension; medical big data research;
Conference_Titel :
Big Data Computing Service and Applications (BigDataService), 2015 IEEE First International Conference on
Conference_Location :
Redwood City, CA
DOI :
10.1109/BigDataService.2015.37