A Machine Learning Approach to Predict Autism Spectrum Disorder
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Cites methods from "A Machine Learning Approach to Pred..."
...In addition, no study has evaluated in detail the early detection based on the ASD datasets, while we used a range of metrics (AUROC, kappa statistics and logloss) to assess this [2], [38], [39] (see Table 13)....
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...[38] developed an autism prediction model by merging Random Forest-CART (RF-CART) and Random Forest-ID3 (RF-ID3) and their proposed models predicted ASD with 92....
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...and adult datasets were explored and ranked which were not shown properly in the previous studies [2], [38], [39]...
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References
14,830 citations
"A Machine Learning Approach to Pred..." refers background in this paper
...This somewhat counter intuitive strategy turns out to perform very well compared to many other classifiers, including discriminant analysis, support vector machines and neural networks, and is robust against over-fitting [18]....
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2,447 citations
"A Machine Learning Approach to Pred..." refers methods in this paper
...To develop an effective predictive model, AQ-10 dataset was used which consists of three different datasets based on AQ-10 screening tool questions [16]....
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967 citations
"A Machine Learning Approach to Pred..." refers methods in this paper
...For example, in [3] Cruz et al tried to diagnose cancer using ML while in [4] Khan et al used ML to predict if...
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583 citations
"A Machine Learning Approach to Pred..." refers methods in this paper
...Heinsfeld [12] applied deep learning algorithm and neural network to...
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