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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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URIhttp://purl.tuc.gr/dl/dias/7E9617F7-A334-47FE-AD9B-819164C9894D-
Identifierhttps://doi.org/10.1145/3444757.3485101-
Identifierhttps://dl.acm.org/doi/10.1145/3444757.3485101-
Languageen-
Extent5 pagesen
TitleData-driven decision support for autism diagnosis using machine learningen
CreatorBatsakis Sotiriosen
CreatorΜπατσακης Σωτηριοςel
CreatorAdamou Mariosen
CreatorTachmazidis Iliasen
CreatorAntoniou, Grigorisen
CreatorKehagias Thanasisen
PublisherAssociation for Computing Machinery (ACM)en
Content SummaryThis 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.en
Type of ItemΔημοσίευση σε Συνέδριοel
Type of ItemConference Publicationen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2023-06-02-
Date of Publication2021-
SubjectAutismen
SubjectClinical decision supporten
Bibliographic CitationS. 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.en

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