Abstract
Heart disease is the most leading cause of death in most developed countries among young adults and aged peoples. Sometimes, even after spending enormous amount of money for treatment, the patient cannot be saved due to their medical condition. Doctors and hospitals in the verge of finding new techniques and methodologies in treating patients following applicable procedures. With the emerging latest medical devices, in recent days, the diagnosis is mostly data-oriented. The historical readings of patient are recorded, and suitable diagnoses are administered to increase the chance survivability. Such a well-defined heart disease-based readings are provided in the UCI heart disease datasets. In this article, we are motivated to perform exploratory data analysis to uncover interesting patterns in the datasets. The patterns are illustrated as a graphs and charts throughout this article.
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Duvvada, S.R. (2022). Graphical Interpretation and Multi-dimensional Data Visualization on Heart Disease Dataset. In: Goar, V., Kuri, M., Kumar, R., Senjyu, T. (eds) Advances in Information Communication Technology and Computing. Lecture Notes in Networks and Systems, vol 392. Springer, Singapore. https://doi.org/10.1007/978-981-19-0619-0_14
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DOI: https://doi.org/10.1007/978-981-19-0619-0_14
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