Ivo H. Pineda

H-Tree: A data structure for fast path-retrieval in rooted trees.

When repeatedly searching on a depth-first or breath-first search fashion, some nodes are visited many times, as every search requires to start at the root. By providing a way to arrange the data in a different manner and using a hash table as the primary data structure, it is possible to get average lookup times of a path, from the root to any node in constant time, although a disadvantage arises when looking at the memory needs of the approach. We propose a structure called H-tree created to reduce the time to extract a path from a rooted tree.

System Development Ontology to Discover Lifestyle Patterns Associated with NCD

The volume of biomedical spatial information available on line increases day by day, need to be exploited and shared by users in different knowledge areas. Although classical information retrieval techniques are efficient, they are not appropriate enough, and that is why in recent years the scientific community has focused on creating new semantic-based approaches to answer users’ queries. In this article the problem of chronic noncommunicable diseases (NCDs) is addressed based on Semantic Web ontologies. NCDs, according WHO, cause 36 million deaths annually affecting any gender and age groups worldwide. Moreover, tobacco and alcohol addictions, physical inactivity and unhealthy diets represent major risk factors. Considering the seriousness of the problem globally, there are already underway government strategies to reduce risk factors and early detection and timely treatment. In particular, we propose an ontologies system for knowledge generation of patterns associated with lifestyle in NCDs. The system consists of the following ontologies: GeoOntoMex, HealthOntoMex, NutritionalOntoMex, PhysicalActivityOntoMex, OntoENTRiskFactors and OntoMedHistory. Also, the system of ontologies provides relevant information on time usage, food and tobacco-alcohol consumption and demographics aspects as lifestyle key dimensions. Furthermore, the system will facilitate the integration of data from different domains for decision making about lifestyle transformation.

Deducting Lifestyle Patterns by Ontologies' SWRL Rules

The volume of biomedical spatial information available on line increases day by day, which need to be exploited and shared by users in different knowledge areas. NCDs kill 36 million people each year and considering the seriousness of the problem globally, there are already underway government strategies to reduce risk factors and early detection and timely treatment. In this article, its discussed the problem of the NCDs using Semantic Web tools. The proposed system consists of six ontologies which formalize concepts related to people, physical activity, NCDs, nutrition, geographic regions and symptoms. Furthermore, the system will facilitate the integration of data from different domains by using SWRL rules for decision making about lifestyle transformation.

Development of an Ontologies System for Spatial Biomedical Applications

In this paper a process of creating ontologies system based on other existing ontologies is described, in order to response biomedical spatial queries on the Web. GeOntoMex is a Mexican spatial ontology, which is structured according to its political-administrative division, in addition, axioms are defined to represent the spatial relationships between geographic entities. Moreover, the Health Onto Mex ontology, whose structure corresponds to the INEGIs taxonomy (National Institute of Statistics and Geography) health services, is presented. Later, a system based on the aforementioned ontologies is shown. The system named Geo Health Onto Mex, could lead to more accurate user queries that requires a specific medical service in a given geographical area.

A Classification Model with Corpus Enrichment for Toponym Disambiguation

This paper presents a method based on information retrieval to enrich corpus using bootstrapping techniques. A supervised corpus manually validated is provided, and then snippets are obtained from Web in order to increase the size of the initial corpus. Although this technique has already been reported in the literature, the main objective of this work is to apply it under the specific task of GEO/NO-GEO toponym disambiguation.The disambiguation procedure is evaluated by a classification model observing favorable results.

Authic: Computational tool for children with autistic spectrum disorder

The AUTHIC project is part of assistive technologies and it aims to develop tools which aid children with autism spectrum disorder (ASD) to understand and interpret facial expressions associated with an emotion, through interactive games supervised by a therapist. Since research is translational, health sciences findings in understanding emotion and the universality of facial expression support the multimedia applications development designed by user-centered methodologies and gamification. Learning routines enable training of ASD children to identify emotions in an interactive and entertaining way.

Mining Biomedical Data from MexRisc

In this paper, it is presented a support system for decision making to diabetes prevention. Using MexRisc platform, a large number of data is collected, and then preprocessing data techniques are applied in order to do a classification process.