Data-Driven Decision Support for Adult Autism Diagnosis Using Machine Learning

Sotirios Batsakis, Marios Adamou, Ilias Tachmazidis, Sarah Jones, Sofya Titarenko, Grigoris Antoniou, Thanasis Kehagias

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Adult referrals to specialist autism spectrum disorder diagnostic services have increased in recent years, placing strain on existing services and illustrating the need for the development of a reliable screening tool, in order to identify and prioritize patients most likely to receive an ASD diagnosis. In this work a detailed overview of existing approaches is presented and a data driven analysis using machine learning is applied on a dataset of adult autism cases consisting of 192 cases. Our results show initial promise, achieving total positive rate (i.e., correctly classified instances to all instances ratio) up to 88.5%, but also point to limitations of currently available data, opening up avenues for further research. The main direction of this research is the development of a novel autism screening tool for adults (ASTA) also introduced in this work and preliminary results indicate the ASTA is suitable for use as a screening tool for adult populations in clinical settings.
Original languageEnglish
Pages (from-to)224-243
Number of pages20
JournalDigital
Volume2
Issue number2
Early online date11 May 2022
DOIs
Publication statusPublished - 1 Jun 2022

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