Data Visualization with IBM Watson Analytics for Global Cancer Trends Comparison from World Health Organization

Kelvin K. F. Tsoi, Felix C. H. Chan, Hoyee W. Hirai, Gary K. S. Keung, Yong-Hong Kuo, Samson Tai and Helen M. L. Meng
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Kelvin K. F. Tsoi: Stanley Ho Big Data Decision Analytics Research Centre and Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
Felix C. H. Chan: Stanley Ho Big Data Decision Analytics Research Centre, Chinese University of Hong Kong, Hong Kong, China
Hoyee W. Hirai: Stanley Ho Big Data Decision Analytics Research Centre, Chinese University of Hong Kong, Hong Kong, China
Gary K. S. Keung: Stanley Ho Big Data Decision Analytics Research Centre, Chinese University of Hong Kong, Hong Kong, China
Yong-Hong Kuo: Stanley Ho Big Data Decision Analytics Research Centre, Chinese University of Hong Kong, Hong Kong, China
Samson Tai: IBM China/Hong Kong Limited, Hong Kong, China
Helen M. L. Meng: Stanley Ho Big Data Decision Analytics Research Centre and Department of Systems Engineering and Engineering Management, Chinese University of Hong Kong, Hong Kong, China

International Journal of Healthcare Information Systems and Informatics (IJHISI), 2018, vol. 13, issue 1, 45-54

Abstract: Visual analytics is widely used to explore data patterns and trends. This work leverages cancer data collected by World Health Organization (WHO) across a hundred of cancer registries worldwide. In this study, the authors present a visual analytics platform, IBM Watson Analytics, to explore the patterns of global cancer incidence. They included 26 forms of cancers from eight different geographic regions which are United States, the United Kingdom, Costa Rica, Sweden, Croatia, Japan, Hong Kong and China (Shanghai). An interactive interface was applied to plot a choropleth map to show global cancer distribution, and line charts to demonstrate historical cancer trends over 29 years. Subgroup analyses were conducted for different age groups. With real-time interactive features, one can easily explore the data with a selection of any cancer type, gender, age group, or geographical region. This platform is running on the cloud, so it can handle data in huge volumes, and is accessible by any computer connected to the Internet. IBM Watson Analytics released a latest version named “IBM Watson Analytics New User Experience” in the end of 2016. The new version streamlined the process to add data, discover data meaning and display result visually. The authors discuss the new features in the end of this paper.

Date: 2018
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