Cervical cancer is currently the fourth most frequent type of cancer in women. A large number of techniques from the Artificial Intelligence (AI) such as Neuronal Networks, Support Vector Machines (SVM), Decision Trees and others; have been used to deal with the problem of predicting this disease. The following paper shows the cervical cancer risk prediction, by implementing a probabilistic model based on Bayesian Networks and using 322 instances where we could retrieve 15 different features that are known information from each patient. The tests were made using the 40% of the whole dataset, confusion matrix and AUC indicator. The results show that this work has raised a 96% of success rate as well as 0.9864 in terms of the AUC indicator, in addition to this, the results suggest that Bayesian Networks are able to reach a high performance and provide transparency during the inference proc...

Infants with Autism Spectrum Disorder (ASD) need special therapies and tools to develop their skills. In many cases, these are not available due to socioeconomic factors, Picture Ex-change Communication System (PECS) is one of the most used tools due to its ease of use and good results. In this study we propose a methodology for developing a mobile application for interaction of infants with ASD with six phases, simultaneously we have created a technological tool called CMI, a mobile application for interaction of infants with ASD that adopts all the features of the traditional PECS and adding new functionalities. Twenty-five infants of varying severity participated in its implementation and received family support for more than a month. The results showed that there was an improvement of more than 15% in the preparation of materials, a reduction in the complexity of use and an increase ...