The Development of CancerAtlas Data Visualization on Number of Cancer deaths Worldwide Analysis

Authors

  • Isyraf Iskandar
  • Norisan Abd Karim College of Computing, Informatics and Mathematics, UiTM Shah Alam
  • Fauziah Redzuan https://orcid.org/0009-0009-3964-6857
  • Rogayah Abdul Majid

Abstract

Cancer is a highly lethal and challenging disease that has tremendous effects on the death rates of the people across the globe. However, the heterogeneity in cancer types as well as their respective death rates among the regions makes it very difficult to understand the global cancer map. CancerAtlas: The Data Visualization on Cancer Deaths Cases Analysis project aims at raising the awareness about the patterns in cancer death rates worldwide and also regional inequalities. The project uses data analytics to create informative infographics on cancer death in the world, which allows us to reflect this complicated data in an understandable way. Using the CancerAtlas dashboard, users can interactively assess, compare, and analyze the cancer mortality rates in different areas, and different age groups with various types of cancer. Usability testing showed that the dashboard is very user-friendly, and it was so easy to understand the presented information including predictive analysis. This implies that data analytics, data visualization and predictive analysis are very powerful tools for creating public awareness regarding the global cancer trends. Since the CancerAtlas dashboard possesses great potential, it is recommended that future versions of the project include real-time data to deliver live visualizations and forecasts, thereby making the insights obtained from the data more accurate and also relevant.

Keywords: Cancer mortality rates, Data visualization, Predictive analysis, Data analytics

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Published

2025-06-17

How to Cite

Isyraf Iskandar, KARIM, N., Fauziah Redzuan, & Rogayah Abdul Majid. (2025). The Development of CancerAtlas Data Visualization on Number of Cancer deaths Worldwide Analysis. Applied Mathematics and Computational Intelligence (AMCI), 14(2), 119–134. Retrieved from https://ejournal.unimap.edu.my/index.php/amci/article/view/1186

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