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              <text>Transforming Pediatric Healthcare with CKD using AI: A Systematic Mapping</text>
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              <text>Abnormalities; AI; Children; chronic kidney disease (CKD); Deep Learning; Machine Learning; Ultrasound (US)</text>
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              <text>Artificial intelligence has been used on a much larger scale, from self-driving cars to biometrics. The daily lifestyle of civilization has changed dramatically due to scientific growth. AI has been pushed to a wide range of applications rather than limited to certain areas and has benefited the health industry, resulting in improved outcomes. Heuristics, support vector machines, artificial neural networks, and natural language processing are some of the AI approaches employed. Kidney diseases and treatment can be challenging, especially when working with youngsters. Children with Chronic Kidney Disease (CKD) experience a wide range of symptoms classified as either transitory or nosologic. Some of its traits influence not only during childhood but also during adulthood in the long run. This study will focus on strategies utilized to identify, predict, and categorize the impacts of pediatric kidney disorders in terms of aetiology, clinical features, and medicines that might assist children in transition to adulthood smoothly.   2023 IEEE.</text>
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              <text>Kausar F.; Ramamurthy B.</text>
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              <text>Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/InC457730.2023.10263186" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/InC457730.2023.10263186&lt;/a&gt;
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              <text>ISBN: 979-835033577-4</text>
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              <text>Kausar F., CHRIST(Deemed to Be Univeristy), Dept. Computer Science, Bangalore, India; Ramamurthy B., CHRIST(Deemed to Be Univeristy), Dept. Computer Science, Bangalore, India</text>
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