Data-driven decision support for autism diagnosis using machine learning
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Adamou, M
Tachmazidis, I
Antoniou, G
Kehagias, T
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Virtual Event Tunisia
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Abstract
This paper describes work in progress about using AI technologies to support diagnostic decision making. In particular, we analyse clinical data of past cases to develop a data-driven prediction model for future cases. To do so, we use a versatile AutoML platform that applies a multitude of machine learning algorithms and their configurations. Our results show initial promise, but also point to limitations of currently available data, opening up avenues for further research.
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MEDES '21: Proceedings of the 13th International Conference on Management of Digital EcoSystems
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© 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in MEDES '21: Proceedings of the 13th International Conference on Management of Digital EcoSystems, ISBN: 978-1-4503-8314-1, https://doi.org/10.1145/3444757.3485101
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Artificial intelligence
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Batsakis, S; Adamou, M; Tachmazidis, I; Antoniou, G; Kehagias, T, Data-driven decision support for autism diagnosis using machine learning, MEDES '21: Proceedings of the 13th International Conference on Management of Digital EcoSystems, 2021, pp. 30-34