Abstract
Computer based systems provides almost unlimited data storage, however, to be useful information needs to be processed and represented by suitable visualization solutions. A better visualization of information is necessary to browse and understand voluminous and complex data, such as health data. Therefore, new data visualization techniques must be investigated so that the vast amount of information makes sense for healthcare professionals, healthcare administrators and patients. More accurate and interpretative information through suitable visualization methods could, for example, contribute to mitigate problems related to congenital malformation. We investigate the design of information visualization solutions to propose new data visualization dashboards to support the prediction of congenital anomalies from patient health data. We used a national data source of Brazil. We present the design and preliminary evaluation results with experts from the health domain and related fields of research. Our proposal is intended to be useful for supporting patients, administrators and health professionals in the prediction activities.
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Notes
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The Apgar score is a method to quickly summarize the health of newborn children, the Apgar1 refers to health at the first minute and Apgar5 in the fifth minute.
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Hyper is a high-volume data processing technology that offers fast analytics performance considering big data.
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1. Strongly disagree, 2. Disagree, 3. Neutral, 4. Agree, 5. Strongly agree.
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de Almeida, T.A., Rosa, F.d.F., Bonacin, R. (2021). Designing Data Visualization Dashboards to Support the Prediction of Congenital Anomalies. In: Yamamoto, S., Mori, H. (eds) Human Interface and the Management of Information. Information Presentation and Visualization. HCII 2021. Lecture Notes in Computer Science(), vol 12765. Springer, Cham. https://doi.org/10.1007/978-3-030-78321-1_12
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