Journal ArticleDOI
Predictive assessment of autism using unsupervised machine learning models
TLDR
This paper used competitive learning networks and unsupervised data clustering methods to model the differential grading in childhood autistic rating scale CARS-based assessment.Abstract:Â
The application of different artificial intelligence models in clinical decision support systems has been a research topic which mainly focuses on the diagnosis method. In this paper we describe the application of unsupervised machine learning models in decision supportive tools for predictive grading of autistic disorder. We used competitive learning networks and unsupervised data clustering methods to model the differential grading in childhood autistic rating scale CARS-based assessment. Modelling of conventional score-based assessment using unsupervised learning methods is the novelty in this work. Self-organisation feature map SOM with single input and four output units perform with a predictive ability of 100% during resubstitution testing.read more
Citations
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Journal ArticleDOI
Machine learning in autistic spectrum disorder behavioral research: A review and ways forward
TL;DR: This article critically analyses recent investigative studies on autism, not only articulating the aforementioned issues in these studies but also recommending paths forward that enhance machine learning use in ASD with respect to conceptualization, implementation, and data.
Journal ArticleDOI
A new machine learning model based on induction of rules for autism detection.
Fadi Thabtah,David Peebles +1 more
TL;DR: Empirical results show that a new machine learning method called Rules-Machine Learning offers classifiers with higher predictive accuracy, sensitivity, harmonic mean, and specificity than those of other machine learning approaches such as Boosting, Bagging, decision trees, and rule induction.
Journal ArticleDOI
Machine learning: the new 'big thing' for competitive advantage
Mohsen Attaran,Promita Deb +1 more
TL;DR: A conceptual model for successful implementation of ML in organisations is proposed and some of the potential benefits and key attributes of successful ML platforms are reviewed and how to overcome some the key implementation challenges are illustrated.
Proceedings ArticleDOI
Early Detection of Autism by Extracting Features: A Case Study in Bangladesh
TL;DR: This work collected individual samples of various children from their parents between 16 to 30 months of different residents using Autism Barta apps by web and fieldwork at Savar, Bangladesh to explore significant features of normal and autism of divisional regions in Bangladesh.
Journal ArticleDOI
A clustering approach for autistic trait classification.
TL;DR: A new semi-supervised ML framework approach called Clustering-based Autistic Trait Classification (CATC) is proposed that uses a clustering technique and that validates classifiers using classification techniques that identifies potential autism cases based on their similarity traits as opposed to a scoring function used by many ASD screening tools.
References
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Book
Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence
TL;DR: This text provides a comprehensive treatment of the methodologies underlying neuro-fuzzy and soft computing with equal emphasis on theoretical aspects of covered methodologies, empirical observations, and verifications of various applications in practice.
Journal ArticleDOI
Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review]
TL;DR: Interestingly, neuro fuzzy and soft computing a computational approach to learning and machine intelligence that you really wait for now is coming.
Journal ArticleDOI
Toward objective classification of childhood autism: Childhood Autism Rating Scale (CARS).
TL;DR: In 1966, when an outpatient treatment program for autistic children and their families was initiated, there were two major sets of guidelines for diagnosing the children who were referred to the program, and the most promising at tempt to translate the Kanner definition into an empirical rating scale was the Rimland Checklist.
Journal ArticleDOI
Performance comparison of neural network training algorithms in modeling of bimodal drug delivery.
Alireza Ghaffari,H. Abdollahi,Mohammad Reza Khoshayand,I. Soltani Bozchalooi,Armin Dadgar,Morteza Rafiee-Tehrani +5 more
TL;DR: Artificial neural network as a multilayer perceptron feedforward network was incorporated for developing a predictive model of the formulations and no significant differences were found between the predictive abilities of IBP and BBP, although, the convergence speed of BBP is three- to four-fold higher than IBP.