Efficient Deep Learning-Based Data-Centric Approach for Autism Spectrum Disorder Diagnosis from Facial Images Using Explainable AI Article Swipe
Mohammad Shafiul Alam
,
Muhammad Mahbubur Rashid
,
Ahmed Rimaz Faizabadi
,
Hasan Firdaus Mohd Zaki
,
Tasfiq E. Alam
,
Md Shahin Ali
,
Kishor Datta Gupta
,
Md Manjurul Ahsan
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/technologies11050115
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/technologies11050115
The research describes an effective deep learning-based, data-centric approach for diagnosing autism spectrum disorder from facial images. To classify ASD and non-ASD subjects, this method requires training a convolutional neural network using the facial image dataset. As a part of the data-centric approach, this research applies pre-processing and synthesizing of the training dataset. The trained model is subsequently evaluated on an independent test set in order to assess the performance matrices of various data-centric approaches. The results reveal that the proposed method that simultaneously applies the pre-processing and augmentation approach on the training dataset outperforms the recent works, achieving excellent 98.9% prediction accuracy, sensitivity, and specificity while having 99.9% AUC. This work enhances the clarity and comprehensibility of the algorithm by integrating explainable AI techniques, providing clinicians with valuable and interpretable insights into the decision-making process of the ASD diagnosis model.
Related Topics
Concepts
Computer science
Artificial intelligence
Convolutional neural network
Autism spectrum disorder
Machine learning
Deep learning
CLARITY
Training set
Autism
Data set
Set (abstract data type)
Pattern recognition (psychology)
Psychology
Developmental psychology
Biochemistry
Programming language
Chemistry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/technologies11050115
- https://www.mdpi.com/2227-7080/11/5/115/pdf?version=1693376806
- OA Status
- gold
- Cited By
- 22
- References
- 59
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386303350
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386303350Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/technologies11050115Digital Object Identifier
- Title
-
Efficient Deep Learning-Based Data-Centric Approach for Autism Spectrum Disorder Diagnosis from Facial Images Using Explainable AIWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-29Full publication date if available
- Authors
-
Mohammad Shafiul Alam, Muhammad Mahbubur Rashid, Ahmed Rimaz Faizabadi, Hasan Firdaus Mohd Zaki, Tasfiq E. Alam, Md Shahin Ali, Kishor Datta Gupta, Md Manjurul AhsanList of authors in order
- Landing page
-
https://doi.org/10.3390/technologies11050115Publisher landing page
- PDF URL
-
https://www.mdpi.com/2227-7080/11/5/115/pdf?version=1693376806Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2227-7080/11/5/115/pdf?version=1693376806Direct OA link when available
- Concepts
-
Computer science, Artificial intelligence, Convolutional neural network, Autism spectrum disorder, Machine learning, Deep learning, CLARITY, Training set, Autism, Data set, Set (abstract data type), Pattern recognition (psychology), Psychology, Developmental psychology, Biochemistry, Programming language, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
22Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 10, 2024: 10, 2023: 2Per-year citation counts (last 5 years)
- References (count)
-
59Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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