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Az-Zahra, Marion
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Computer Science & IT Control & Systems Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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A Glimpse to the Future: Identifying Stroke Risk Factors Using Data Visualization for Stroke Prediction Az-Zahra, Marion
Engineering Science Letter Vol. 3 No. 01 (2024): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/esl.v3i01.470

Abstract

According to the World Health Organization (WHO), stroke stands as the second leading cause of death, accounting for 11 percent of total deaths in the world. This study identifies risk factors associated with stroke that could help predict the likelihood of a person getting a stroke by assessing input parameters such as gender, age, medical conditions related to stroke and cardiac disease, smoking status, body mass index, and average glucose level, among others. The results, presented with data visualization, showed that the above risk factors were significant in signifying stroke incidence.
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