Taguchi recomienda el uso de arreglos ortogonales para hacer matrices que contengan los controles y los factores de ruido en el diseño de experimentos. Taguchi method with Orthogonal Arrays reducing the sample size from. , to only seleccionó utilizando el método de Taguchi con arreglos ortogonales. Taguchi, el ingeniero que hizo los arreglos ortogonales posible con el fin de obtener productos robustos.

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Feed-forward Networks have been used for a great variety of medical applications such as diagnosis of appendicitis, dementia, myocardial infarction, pulmonary embolism, back pain and skin disorders among others [24].

It was found that the items “Showing”, “Shared enjoyment in Interaction” and “Frequency of vocalization directed to others”, are the areas of highest impact for Autism diagnosis.

It is interesting to see that the 3 high impact factors A2, B5 and B9, one medium impact factor B1 and one low impact factor B10 are included in Wall’s items as well.

Metodo Taguchi – VideoZoos

It makes no sense to divide the orthogonal array of 27 cases into two parts training and validation txguchi, because the 27 cases are meant to be the most representative combinations in this method. Design of experiments DOE is the methodology that defines several conditions for an experiment with multiple variables.

This conventionally requires lengthy information processing and technical understanding of each of the areas evaluated in the tools. It can be said that Showing, Shared enjoyment in Interaction and Frequency of ortogonalse directed to others are the three items of high impact for Autism detection.

Centers for Disease Control and Prevention. Since both inputs and desired outputs are available, a supervised artificial neural network was created using Matlab software [32]. Artificial Neural Networks may be able to provide the approach needed to detect Autism Spectrum Disorders ASD by identifying the highest impact factors that could help detecting it at early stages of children’s development.

The robustness of the Mahalanobis-Taguchi System to different arrays that could be used to discriminate variables in a study, is evaluated. ANN must be trained with examples either supervised where both the input and the desired output are entered or unsupervised where the desired output is unknown. Different modules and tasks of the test are mainly oriented towards evaluating the level of communication and specific behaviors in social interactions.


In Mexico there is not a national study that can provide the Ortogoonales prevalence [4], but some nongovernmental associations estimate that 1 in children has been diagnosed with Autism in Mexico [5].

The training samples were selected as an orthogonal array using the Taguchi method to pick the least number of combinations that would be a representative sample suitable for training.

The results showed that this method is not robust to the different arrays that could be used. The second level corresponds to the evaluation and diagnostic of ASD that should be performed by health specialists in areas such as Psychiatry or Psychology who can carry out a clinical diagnosis based on the fifth edition of the Diagnostic and Statistical Manual also known as the DSM-V [6] and the tenth revision of the International Classification of Diseases also known as the ICD [10] ; or even use screening and diagnostic tools validated internationally.

As every tool, ANN should be analyzed before using it with each specific situation. It usually begins during the first 24 months of life; this period is defined as crucial for the maturation of human neural circuits. Van Der Smagt Only when the three sums reach the threshold or cutoff, then the child can be diagnosed with Autism. It usually takes between 30 to 60 minutes to be applied and the test consists of activities performed by the child in interaction of the expert who observes him and assigns a grade [18].

The objective of the instrument is not to evaluate knowledge abilities in the subject but rather to evaluate if the subject wants to participate in a social exchange [19]. Therefore the complete orthogonal array of 27 cases was taken as training data.

Evaluación de la Robustez del sistema Mahalanobis-Taguchi a diferentes Arreglos Factoriales.

The more examples it is trained with, the higher precision should be achieved to solve new cases. Once the ANN was trained and validated, the following step was to classify the 12 factors through their impact on diagnosis. The ortogonalex is answered by the children’s parents. It is clear that “definitely abnormal” in two areas is not exactly the same as “mildly abnormal” in four areas since mildly abnormal could be easier to overcome than a definitely abnormal.


An Introduction to Neural Network [online]. The full factorial design is given by. Agreglos is important to notice that it is a common practice for ANN training to perform a cross validation method to estimate the performance of the learning algorithm.

The algorithm also counts the following 7 items to evaluate the child’s social interaction: Artificial Neural Networks ANN are computational models based on a simplified version of biological neural networks with which they share some characteristics like adaptability to learn, generalization, data organization and parallel processing.

This algorithm evaluation is shown as the last column in Table 4.

Genichi Taguchi by Alfonso Armendariz on Prezi

Autism diagnosis requires validated diagnostic tools employed by mental health professionals with expertise in autism spectrum disorders. Since the information of column 13 is included in the other 12, only tagucui columns were used.

Tests and results from the ANN were observed to find the factor’s that consistently generate gin Autism diagnosis.

The full factorial design is given by Where m is the number of factors and L is the number of levels for each factor or the possible values each factor can rareglos. The output value is a number in the range of 0 and 1 because the activation function was a hyperbolic tangent sigmoid function see Figure 5for this reason, the output values above or equal to 0.

Wing, “The autistic spectrum”, The lancet,pp. The next step was to reduce the number of cases to train the ANN, it has been mentioned that the L 27 orthogonal array should be selected for the number of parameters and states.

Table 5 Once the ANN was trained and validated, the following step was to classify the 12 factors through their impact on diagnosis. This is the reason why they are called high impact factors.