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A Fuzzy Prescreening Tool to Assist in the Diagnosis of High Functioning Individuals on the Autism Spectrum Who Present with Mental Health Comorbidities

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Advances in Computational Intelligence Systems (UKCI 2022)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1454))

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Abstract

Autism Spectrum Disorder is a neurological developmental disorder that effects at least 1% of the population, the majority of cases are high functioning individuals who struggle to get positive diagnoses that are vital to obtain community support. In this study, we have created and tested a Fuzzy Inferencing System to support clinicians, psychologists, family members and relevant stake holders to increase the chances for high functioning individuals to get a referral for full assessment to determine an autism diagnosis.

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References

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Author information

Authors and Affiliations

  1. Institute of Artificial Intelligence, School of Computer Science and Informatics, De Montfort University, Leicester, LE1 9BH, UK

    Philip Smith & Sarah Greenfield

Authors
  1. Philip Smith
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  2. Sarah Greenfield
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Corresponding author

Correspondence to Sarah Greenfield .

Editor information

Editors and Affiliations

  1. Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK

    George Panoutsos

  2. Department of Automatic Control and Systems Engineering, Head of the Intelligent Systems Research Laboratory, The University of Sheffield, Sheffield, South Yorkshire, UK

    Mahdi Mahfouf

  3. Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, South Yorkshire, UK

    Lyudmila S Mihaylova

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Smith, P., Greenfield, S. (2024). A Fuzzy Prescreening Tool to Assist in the Diagnosis of High Functioning Individuals on the Autism Spectrum Who Present with Mental Health Comorbidities. In: Panoutsos, G., Mahfouf, M., Mihaylova, L.S. (eds) Advances in Computational Intelligence Systems. UKCI 2022. Advances in Intelligent Systems and Computing, vol 1454. Springer, Cham. https://doi.org/10.1007/978-3-031-55568-8_5

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