Identifying the semantics of eligibility criteria of clinical trials based on relevant medical ontologies

An important objective of the INTEGRATE project1 is to build tools that support the efficient execution of post-genomic multi-centric clinical trials in breast cancer, which includes the automatic assessment of the eligibility of patients for available trials. The population suited to be enrolled in a trial is described by a set of free-text eligibility criteria that are both syntactically and semantically complex. At the same time, the assessment of the eligibility of a patient for a trial requires the (machineprocessable) understanding of the semantics of the eligibility criteria in order to further evaluate if the patient data available for example in the hospital EHR satisfies these criteria. This paper presents an analysis of the semantics of the clinical trial eligibility criteria based on relevant medical ontologies in the clinical research domain: SNOMED-CT, LOINC, MedDRA. We detect subsets of these widely-adopted ontologies that characterize the semantics of the eligibility criteria of trials in various clinical domains and compare these sets. Next, we evaluate the occurrence frequency of the concepts in the concrete case of breast cancer (which is our first application domain) in order to provide meaningful priorities for the task of binding/mapping these ontology concepts to the actual patient data. We further assess the effort required to extend our approach to new domains in terms of additional semantic mappings that need to be developed.

Essentials in Ontology Engineering: Methodologies, Languages, and Tools

In the beginning of the 90s, ontology development was similar to an art: ontology developers did not have clear guidelines on how to build ontologies but only some design criteria to be followed. Work on principles, methods and methodologies, together with supporting technologies and languages, made ontology development become an engineering discipline, the so-called Ontology Engineering. Ontology Engineering refers to the set of activities that concern the ontology development process and the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. Thanks to the work done in the Ontology Engineering field, the development of ontologies within and between teams has increased and improved, as well as the possibility of reusing ontologies in other developments and in final applications. Currently, ontologies are widely used in (a) Knowledge Engineering, Artificial Intelligence and Computer Science, (b) applications related to knowledge management, natural language processing, e-commerce, intelligent information integration, information retrieval, database design and integration, bio-informatics, education, and (c) the Semantic Web, the Semantic Grid, and the Linked Data initiative. In this paper, we provide an overview of Ontology Engineering, mentioning the most outstanding and used methodologies, languages, and tools for building ontologies. In addition, we include some words on how all these elements can be used in the Linked Data initiative.

Sistema de e-learning en el entorno AFRICA BUILD Portal

Diversos estudios consideran que las claves para el desarrollo técnico, social y económico de los países en desarrollo, y en especial en África, son la educación, la investigación y la innovación. No obstante, en el ámbito sanitario en particular, la formación e investigación en África sigue siendo escasa por diversos motivos. Por un lado, los investigadores africanos encuentran dificultades añadidas para obtener financiación frente a investigadores en países de desarrollo. Y, por otro lado, los investigadores no disponen de las herramientas y tecnologías adecuadas para acceder a información relevante para su trabajo. En este contexto, el proyecto AFRICA BUILD tiene como principal objetivo mejorar y fomentar la investigación y educación sanitaria en África a través de las nuevas tecnologías. Uno de los resultados principales de este proyecto es el AFRICA BUILD Portal (ABP), que pretende ser un punto de encuentro para los investigadores africanos, donde podrán encontrar un amplio abanico de herramientas que les permita no sólo mejorar su educación, sino compartir conocimientos con otros investigadores. Este portal, que está actualmente en desarrollo, pretende fomentar la comunicación entre instituciones africanas y les proveerá herramientas biomédicas avanzadas. En este Trabajo de Fin de Grado se han marcado como principal objetivo la mejora del sistema de e-learning que existía en el ABP. El nuevo sistema será: (i) más potente, óptimo y rico en funcionalidades, (ii) tendrá una importante base social permitiendo a los usuarios aportar información y compartir conocimiento, y (iii) será distribuido y escalable, capaz de integrar distintos gestores de contenidos didácticos como fuentes de información. Los resultados obtenidos son positivos y el nuevo sistema de aprendizaje ha mejorado la usabilidad, funcionalidad y apariencia del anterior. Para concluir, la herramienta posee aún un gran margen de mejora, pero gracias al trabajo realizado el sistema de e-learning es ahora más social, distribuido, escalable e innovador. ---ABSTRACT---Several studies find that the keys to the technical, social and economic development of developing countries, especially in Africa, are education, research and innovation. However, in the health sector in particular, training and research in Africa remains low for various reasons. On the one hand, African researchers experience additional difficulties for funding against researchers in developing countries. And on the other hand, researchers do not have the right tools and technologies to access information relevant to their work. In this context, the AFRICA BUILD project's main objective is to improve and enhance research and health education in Africa through new technologies. One of the main results of this project is the AFRICA BUILD Portal (ABP), which aims to be a meeting point for African researchers, where they can find a wide range of tools that allows them to not only improve their education but to share knowledge with other researchers. This portal, which is currently under development, aims to promote communication between African institutions and will provide advanced biomedical tools. The main objective of this Final Year Project is the improvement of the former elearning system that already existed in the ABP. The new system will be: (i) more powerful, richer in features, (ii) will have an important social base allowing users to contribute information and knowledge sharing; and (iii) will be distributed and scalable, capable of integrating different learning management systems as sources of information. The final results obtained are fairly positive and the new e-learning system has improved its usability, functionality and appearance of the former. To conclude, the tool still has much room for improvement, but thanks to the new features of the improved elearning system has become more social, distributed, scalable and innovative.

A digital framework to build, visualize and analyze a gene expression atlas with cellular resolution in zebrafish early embryogenesis

A gene expression atlas is an essential resource to quantify and understand the multiscale processes of embryogenesis in time and space. The automated reconstruction of a prototypic 4D atlas for vertebrate early embryos, using multicolor fluorescence in situ hybridization with nuclear counterstain, requires dedicated computational strategies. To this goal, we designed an original methodological framework implemented in a software tool called Match-IT. With only minimal human supervision, our system is able to gather gene expression patterns observed in different analyzed embryos with phenotypic variability and map them onto a series of common 3D templates over time, creating a 4D atlas. This framework was used to construct an atlas composed of 6 gene expression templates from a cohort of zebrafish early embryos spanning 6 developmental stages from 4 to 6.3 hpf (hours post fertilization). They included 53 specimens, 181,415 detected cell nuclei and the segmentation of 98 gene expression patterns observed in 3D for 9 different genes. In addition, an interactive visualization software, Atlas-IT, was developed to inspect, supervise and analyze the atlas. Match-IT and Atlas-IT, including user manuals, representative datasets and video tutorials, are publicly and freely available online. We also propose computational methods and tools for the quantitative assessment of the gene expression templates at the cellular scale, with the identification, visualization and analysis of coexpression patterns, synexpression groups and their dynamics through developmental stages.