The aid of machine learning to overcome the classification of real health discharge reports written in Spanish

Hospitals attached to the Spanish Ministry of Health are currently using the International Classification of Diseases 9 Clinical Modification (ICD9-CM) to classify health discharge records. Nowadays, this work is manually done by experts. This paper tackles the automatic classification of real Discharge Records in Spanish following the ICD9-CM standard. The challenge is that the Discharge Records are written in spontaneous language. We explore several machine learning techniques to deal with the classification problem. Random Forest resulted in the most competitive one, achieving an F-measure of 0.876.

Morphological classification of microtidal sand and gravel beaches

A new classification of microtidal sand and gravel beaches with very different morphologies is presented below. In 557 studied transects, 14 variables were used. Among the variables to be emphasized is the depth of the Posidonia oceanica. The classification was performed for 9 types of beaches: Type 1: Sand and gravel beaches, Type 2: Sand and gravel separated beaches, Type 3: Gravel and sand beaches, Type 4: Gravel and sand separated beaches, Type 5: Pure gravel beaches, Type 6: Open sand beaches, Type 7: Supported sand beaches, Type 8: Bisupported sand beaches and Type 9: Enclosed beaches. For the classification, several tools were used: discriminant analysis, neural networks and Support Vector Machines (SVM), the results were then compared. As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer. Finally, an architecture with 30 neurons was chosen. Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid). The results obtained for the discriminant analysis were not as good as those obtained for the other two methods (ANN and SVM) which showed similar success.

Exploring the use of cooperative activities in a language subject to develop students’ social competences at the University

Cooperative learning has been successfully implemented in the last 60 years for teaching at different educational levels including the Higher Studies due to its solid theoretical foundation, the principles it proposes and its practical applications. The purpose of this article is to offer a proposal for some cooperative activities that allow students to work in small groups in a language subject in order to learn not only contents but also putting into practice what they learn, i.e., they learn by being active. This article discusses how the said activities make it possible for students to work with the main principles of cooperative learning, i.e.: positive interdependence, face-to-face interaction, individual and group accountability, interpersonal and small-group skills and group processing. Moreover, this research will also point out that the proposed activities allow students to acquire some of the social competences required in the labour market such as leadership, conflict solving and cooperation.