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An XAI Based Autism Detection: The Context Behind the Detection

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Brain Informatics (BI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12960))

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Abstract

With the rapid growth of the Internet of Healthcare Things, a massive amount of data is generated by a broad variety of medical devices. Because of the complex relationship in large-scale healthcare data, researchers who bring a revolution in the healthcare industry embrace Artificial Intelligence (AI). In certain cases, it has been reported that AI can do better than humans at performing healthcare tasks. The data-driven black-box model, on the other hand, does not appeal to healthcare professionals as it is not transparent, and any biasing can hamper the performance the prediction model for the real-life operation. In this paper, we proposed an AI model for early detection of autism in children. Then we showed why AI with explainability is important. This paper provides examples focused on the Autism Spectrum Disorder dataset (Autism screening data for toddlers by Dr Fadi Fayez Thabtah) and discussed why explainability approaches should be used when using AI systems in healthcare.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Mirpur, Dhaka, 1216, Bangladesh

    Milon Biswas

  2. Institute of Information Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh

    M. Shamim Kaiser & Shamim Al Mamun

  3. Applied Intelligence and Informatics (AII) Lab, Wazed Miah Science Research Centre, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh

    M. Shamim Kaiser, Shamim Al Mamun & Muhammad Arifur Rahman

  4. Department of Computer Science, Nottingham Trent University, Clifton Lane, Nottingham, NG118NS, UK

    Mufti Mahmud

  5. Department of Computer Science and Engineering, Chittagong University, Chittagong, 4331, Bangladesh

    Md. Shahadat Hossain

  6. Department of Physics, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh

    Muhammad Arifur Rahman

Authors
  1. Milon Biswas
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  2. M. Shamim Kaiser
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  3. Mufti Mahmud
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  4. Shamim Al Mamun
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  5. Md. Shahadat Hossain
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  6. Muhammad Arifur Rahman
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Corresponding author

Correspondence to M. Shamim Kaiser .

Editor information

Editors and Affiliations

  1. Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  2. Jahangirnagar University, Dhaka, Bangladesh

    M Shamim Kaiser

  3. University of Padua, Padua, Italy

    Stefano Vassanelli

  4. Tsinghua University, Beijing, China

    Qionghai Dai

  5. Maebashi Institute of Technology, Maebashi, Japan

    Ning Zhong

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Biswas, M., Kaiser, M.S., Mahmud, M., Al Mamun, S., Hossain, M.S., Rahman, M.A. (2021). An XAI Based Autism Detection: The Context Behind the Detection. In: Mahmud, M., Kaiser, M.S., Vassanelli, S., Dai, Q., Zhong, N. (eds) Brain Informatics. BI 2021. Lecture Notes in Computer Science(), vol 12960. Springer, Cham. https://doi.org/10.1007/978-3-030-86993-9_40

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  • DOI: https://doi.org/10.1007/978-3-030-86993-9_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86992-2

  • Online ISBN: 978-3-030-86993-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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