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Data-driven decision support for autism diagnosis using machine learning

Batsakis Sotirios, Adamou Marios, Tachmazidis Ilias, Antoniou, Grigoris, Kehagias Thanasis

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URI: http://purl.tuc.gr/dl/dias/7E9617F7-A334-47FE-AD9B-819164C9894D
Year 2021
Type of Item Conference Publication
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Bibliographic Citation S. Batsakis, M. Adamou, I. Tachmazidis, G. Antoniou and T. Kehagias, “Data-driven decision support for autism diagnosis using machine learning,” in Proceedings of the 13th International Conference on Management of Digital EcoSystems (MEDES 2021), virtual event, 2021, pp. 30–34, doi: 10.1145/3444757.3485101. https://doi.org/10.1145/3444757.3485101
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Conference Publications in Community School of Production Engineering and Management

Summary

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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