e-MIR2: a public online inventory of medical informatics resources

Background. Over the last years, the number of available informatics resources in medicine has grown exponentially. While specific inventories of such resources have already begun to be developed for Bioinformatics (BI), comparable inventories are as yet not available for Medical Informatics (MI) field, so that locating and accessing them currently remains a hard and time-consuming task. Description. We have created a repository of MI resources from the scientific literature, providing free access to its contents through a web-based service. Relevant information describing the resources is automatically extracted from manuscripts published in top-ranked MI journals. We used a pattern matching approach to detect the resources? names and their main features. Detected resources are classified according to three different criteria: functionality, resource type and domain. To facilitate these tasks, we have built three different taxonomies by following a novel approach based on folksonomies and social tagging. We adopted the terminology most frequently used by MI researchers in their publications to create the concepts and hierarchical relationships belonging to the taxonomies. The classification algorithm identifies the categories associated to resources and annotates them accordingly. The database is then populated with this data after manual curation and validation. Conclusions. We have created an online repository of MI resources to assist researchers in locating and accessing the most suitable resources to perform specific tasks. The database contained 282 resources at the time of writing. We are continuing to expand the number of available resources by taking into account further publications as well as suggestions from users and resource developers.

p-medicine: a medical informatics platform for integrated large scale heterogeneous patient data

Secure access to patient data is becoming of increasing importance, as medical informatics grows in significance, to both assist with population health studies, and patient specific medicine in support of treatment. However, assembling the many different types of data emanating from the clinic is in itself a difficulty, and doing so across national borders compounds the problem. In this paper we present our solution: an easy to use distributed informatics platform embedding a state of the art data warehouse incorporating a secure pseudonymisation system protecting access to personal healthcare data. Using this system, a whole range of patient derived data, from genomics to imaging to clinical records, can be assembled and linked, and then connected with analytics tools that help us to understand the data. Research performed in this environment will have immediate clinical impact for personalised patient healthcare.

Note on Friedman's "what informatics is and isn't"

Friedman’s article ‘What informatics is and isn’t’, presents a necessary and timely analysis of the field of informatics.

ACGT: advancing clinico-genomic trials on cancer - four years of experience.

The challenges regarding seamless integration of distributed, heterogeneous and multilevel data arising in the context of contemporary, post-genomic clinical trials cannot be effectively addressed with current methodologies. An urgent need exists to access data in a uniform manner, to share information among different clinical and research centers, and to store data in secure repositories assuring the privacy of patients. Advancing Clinico-Genomic Trials (ACGT) was a European Commission funded Integrated Project that aimed at providing tools and methods to enhance the efficiency of clinical trials in the -omics era. The project, now completed after four years of work, involved the development of both a set of methodological approaches as well as tools and services and its testing in the context of real-world clinico-genomic scenarios. This paper describes the main experiences using the ACGT platform and its tools within one such scenario and highlights the very promising results obtained.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results: We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions: CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems.

Building sustainable capacity for health research in africa through cloud computing applications

Access to information and continuous education represent critical factors for physicians and researchers over the world. For African professionals, this situation is even more problematic due to the frequently difficult access to technological infrastructures and basic information. Both education and information technologies (e.g., including hardware, software or networking) are expensive and unaffordable for many African professionals. Thus, the use of e-learning and an open approach to information exchange and software use have been already proposed to improve medical informatics issues in Africa. In this context, the AFRICA BUILD project, supported by the European Commission, aims to develop a virtual platform to provide access to a wide range of biomedical informatics and learning resources to professionals and researchers in Africa. A consortium of four African and four European partners work together in this initiative. In this framework, we have developed a prototype of a cloud-computing infrastructure to demonstrate, as a proof of concept, the feasibility of this approach. We have conducted the experiment in two different locations in Africa: Burundi and Egypt. As shown in this paper, technologies such as cloud computing and the use of open source medical software for a large range of case present significant challenges and opportunities for developing countries, such as many in Africa.

A model to develop a platform for personalised health applications

Antecedentes Europa vive una situación insostenible. Desde el 2008 se han reducido los recursos de los gobiernos a raíz de la crisis económica. El continente Europeo envejece con ritmo constante al punto que se prevé que en 2050 habrá sólo dos trabajadores por jubilado [54]. A esta situación se le añade el aumento de la incidencia de las enfermedades crónicas, relacionadas con el envejecimiento, cuyo coste puede alcanzar el 7% del PIB de un país [51]. Es necesario un cambio de paradigma. Una nueva manera de cuidar de la salud de las personas: sustentable, eficaz y preventiva más que curativa. Algunos estudios abogan por el cuidado personalizado de la salud (pHealth). En este modelo las prácticas médicas son adaptadas e individualizadas al paciente, desde la detección de los factores de riesgo hasta la personalización de los tratamientos basada en la respuesta del individuo [81]. El cuidado personalizado de la salud está asociado a menudo al uso de las tecnologías de la información y comunicación (TICs) que, con su desarrollo exponencial, ofrecen oportunidades interesantes para la mejora de la salud. El cambio de paradigma hacia el pHealth está lentamente ocurriendo, tanto en el ámbito de la investigación como en la industria, pero todavía no de manera significativa. Existen todavía muchas barreras relacionadas a la economía, a la política y la cultura. También existen barreras puramente tecnológicas, como la falta de sistemas de información interoperables [199]. A pesar de que los aspectos de interoperabilidad están evolucionando, todavía hace falta un diseño de referencia especialmente direccionado a la implementación y el despliegue en gran escala de sistemas basados en pHealth. La presente Tesis representa un intento de organizar la disciplina de la aplicación de las TICs al cuidado personalizado de la salud en un modelo de referencia, que permita la creación de plataformas de desarrollo de software para simplificar tareas comunes de desarrollo en este dominio. Preguntas de investigación RQ1 >Es posible definir un modelo, basado en técnicas de ingeniería del software, que represente el dominio del cuidado personalizado de la salud de una forma abstracta y representativa? RQ2 >Es posible construir una plataforma de desarrollo basada en este modelo? RQ3 >Esta plataforma ayuda a los desarrolladores a crear sistemas pHealth complejos e integrados? Métodos Para la descripción del modelo se adoptó el estándar ISO/IEC/IEEE 42010por ser lo suficientemente general y abstracto para el amplio enfoque de esta tesis [25]. El modelo está definido en varias partes: un modelo conceptual, expresado a través de mapas conceptuales que representan las partes interesadas (stakeholders), los artefactos y la información compartida; y escenarios y casos de uso para la descripción de sus funcionalidades. El modelo fue desarrollado de acuerdo a la información obtenida del análisis de la literatura, incluyendo 7 informes industriales y científicos, 9 estándares, 10 artículos en conferencias, 37 artículos en revistas, 25 páginas web y 5 libros. Basándose en el modelo se definieron los requisitos para la creación de la plataforma de desarrollo, enriquecidos por otros requisitos recolectados a través de una encuesta realizada a 11 ingenieros con experiencia en la rama. Para el desarrollo de la plataforma, se adoptó la metodología de integración continua [74] que permitió ejecutar tests automáticos en un servidor y también desplegar aplicaciones en una página web. En cuanto a la metodología utilizada para la validación se adoptó un marco para la formulación de teorías en la ingeniería del software [181]. Esto requiere el desarrollo de modelos y proposiciones que han de ser validados dentro de un ámbito de investigación definido, y que sirvan para guiar al investigador en la búsqueda de la evidencia necesaria para justificarla. La validación del modelo fue desarrollada mediante una encuesta online en tres rondas con un número creciente de invitados. El cuestionario fue enviado a 134 contactos y distribuido en algunos canales públicos como listas de correo y redes sociales. El objetivo era evaluar la legibilidad del modelo, su nivel de cobertura del dominio y su potencial utilidad en el diseño de sistemas derivados. El cuestionario incluía preguntas cuantitativas de tipo Likert y campos para recolección de comentarios. La plataforma de desarrollo fue validada en dos etapas. En la primera etapa se utilizó la plataforma en un experimento a pequeña escala, que consistió en una sesión de entrenamiento de 12 horas en la que 4 desarrolladores tuvieron que desarrollar algunos casos de uso y reunirse en un grupo focal para discutir su uso. La segunda etapa se realizó durante los tests de un proyecto en gran escala llamado HeartCycle [160]. En este proyecto un equipo de diseñadores y programadores desarrollaron tres aplicaciones en el campo de las enfermedades cardio-vasculares. Una de estas aplicaciones fue testeada en un ensayo clínico con pacientes reales. Al analizar el proyecto, el equipo de desarrollo se reunió en un grupo focal para identificar las ventajas y desventajas de la plataforma y su utilidad. Resultados Por lo que concierne el modelo que describe el dominio del pHealth, la parte conceptual incluye una descripción de los roles principales y las preocupaciones de los participantes, un modelo de los artefactos TIC que se usan comúnmente y un modelo para representar los datos típicos que son necesarios formalizar e intercambiar entre sistemas basados en pHealth. El modelo funcional incluye un conjunto de 18 escenarios, repartidos en: punto de vista de la persona asistida, punto de vista del cuidador, punto de vista del desarrollador, punto de vista de los proveedores de tecnologías y punto de vista de las autoridades; y un conjunto de 52 casos de uso repartidos en 6 categorías: actividades de la persona asistida, reacciones del sistema, actividades del cuidador, \engagement" del usuario, actividades del desarrollador y actividades de despliegue. Como resultado del cuestionario de validación del modelo, un total de 65 personas revisó el modelo proporcionando su nivel de acuerdo con las dimensiones evaluadas y un total de 248 comentarios sobre cómo mejorar el modelo. Los conocimientos de los participantes variaban desde la ingeniería del software (70%) hasta las especialidades médicas (15%), con declarado interés en eHealth (24%), mHealth (16%), Ambient Assisted Living (21%), medicina personalizada (5%), sistemas basados en pHealth (15%), informática médica (10%) e ingeniería biomédica (8%) con una media de 7.25_4.99 años de experiencia en estas áreas. Los resultados de la encuesta muestran que los expertos contactados consideran el modelo fácil de leer (media de 1.89_0.79 siendo 1 el valor más favorable y 5 el peor), suficientemente abstracto (1.99_0.88) y formal (2.13_0.77), con una cobertura suficiente del dominio (2.26_0.95), útil para describir el dominio (2.02_0.7) y para generar sistemas más específicos (2_0.75). Los expertos también reportan un interés parcial en utilizar el modelo en su trabajo (2.48_0.91). Gracias a sus comentarios, el modelo fue mejorado y enriquecido con conceptos que faltaban, aunque no se pudo demonstrar su mejora en las dimensiones evaluadas, dada la composición diferente de personas en las tres rondas de evaluación. Desde el modelo, se generó una plataforma de desarrollo llamada \pHealth Patient Platform (pHPP)". La plataforma desarrollada incluye librerías, herramientas de programación y desarrollo, un tutorial y una aplicación de ejemplo. Se definieron cuatro módulos principales de la arquitectura: el Data Collection Engine, que permite abstraer las fuentes de datos como sensores o servicios externos, mapeando los datos a bases de datos u ontologías, y permitiendo interacción basada en eventos; el GUI Engine, que abstrae la interfaz de usuario en un modelo de interacción basado en mensajes; y el Rule Engine, que proporciona a los desarrolladores un medio simple para programar la lógica de la aplicación en forma de reglas \if-then". Después de que la plataforma pHPP fue utilizada durante 5 años en el proyecto HeartCycle, 5 desarrolladores fueron reunidos en un grupo de discusión para analizar y evaluar la plataforma. De estas evaluaciones se concluye que la plataforma fue diseñada para encajar las necesidades de los ingenieros que trabajan en la rama, permitiendo la separación de problemas entre las distintas especialidades, y simplificando algunas tareas de desarrollo como el manejo de datos y la interacción asíncrona. A pesar de ello, se encontraron algunos defectos a causa de la inmadurez de algunas tecnologías empleadas, y la ausencia de algunas herramientas específicas para el dominio como el procesado de datos o algunos protocolos de comunicación relacionados con la salud. Dentro del proyecto HeartCycle la plataforma fue utilizada para el desarrollo de la aplicación \Guided Exercise", un sistema TIC para la rehabilitación de pacientes que han sufrido un infarto del miocardio. El sistema fue testeado en un ensayo clínico randomizado en el cual a 55 pacientes se les dio el sistema para su uso por 21 semanas. De los resultados técnicos del ensayo se puede concluir que, a pesar de algunos errores menores prontamente corregidos durante el estudio, la plataforma es estable y fiable. Conclusiones La investigación llevada a cabo en esta Tesis y los resultados obtenidos proporcionan las respuestas a las tres preguntas de investigación que motivaron este trabajo: RQ1 Se ha desarrollado un modelo para representar el dominio de los sistemas personalizados de salud. La evaluación hecha por los expertos de la rama concluye que el modelo representa el dominio con precisión y con un balance apropiado entre abstracción y detalle. RQ2 Se ha desarrollado, con éxito, una plataforma de desarrollo basada en el modelo. RQ3 Se ha demostrado que la plataforma es capaz de ayudar a los desarrolladores en la creación de software pHealth complejos. Las ventajas de la plataforma han sido demostradas en el ámbito de un proyecto de gran escala, aunque el enfoque genérico adoptado indica que la plataforma podría ofrecer beneficios también en otros contextos. Los resultados de estas evaluaciones ofrecen indicios de que, ambos, el modelo y la plataforma serán buenos candidatos para poderse convertir en una referencia para futuros desarrollos de sistemas pHealth. ABSTRACT Background Europe is living in an unsustainable situation. The economic crisis has been reducing governments' economic resources since 2008 and threatening social and health systems, while the proportion of older people in the European population continues to increase so that it is foreseen that in 2050 there will be only two workers per retiree [54]. To this situation it should be added the rise, strongly related to age, of chronic diseases the burden of which has been estimated to be up to the 7% of a country's gross domestic product [51]. There is a need for a paradigm shift, the need for a new way of caring for people's health, shifting the focus from curing conditions that have arisen to a sustainable and effective approach with the emphasis on prevention. Some advocate the adoption of personalised health care (pHealth), a model where medical practices are tailored to the patient's unique life, from the detection of risk factors to the customization of treatments based on each individual's response [81]. Personalised health is often associated to the use of Information and Communications Technology (ICT), that, with its exponential development, offers interesting opportunities for improving healthcare. The shift towards pHealth is slowly taking place, both in research and in industry, but the change is not significant yet. Many barriers still exist related to economy, politics and culture, while others are purely technological, like the lack of interoperable information systems [199]. Though interoperability aspects are evolving, there is still the need of a reference design, especially tackling implementation and large scale deployment of pHealth systems. This thesis contributes to organizing the subject of ICT systems for personalised health into a reference model that allows for the creation of software development platforms to ease common development issues in the domain. Research questions RQ1 Is it possible to define a model, based on software engineering techniques, for representing the personalised health domain in an abstract and representative way? RQ2 Is it possible to build a development platform based on this model? RQ3 Does the development platform help developers create complex integrated pHealth systems? Methods As method for describing the model, the ISO/IEC/IEEE 42010 framework [25] is adopted for its generality and high level of abstraction. The model is specified in different parts: a conceptual model, which makes use of concept maps, for representing stakeholders, artefacts and shared information, and in scenarios and use cases for the representation of the functionalities of pHealth systems. The model was derived from literature analysis, including 7 industrial and scientific reports, 9 electronic standards, 10 conference proceedings papers, 37 journal papers, 25 websites and 5 books. Based on the reference model, requirements were drawn for building the development platform enriched with a set of requirements gathered in a survey run among 11 experienced engineers. For developing the platform, the continuous integration methodology [74] was adopted which allowed to perform automatic tests on a server and also to deploy packaged releases on a web site. As a validation methodology, a theory building framework for SW engineering was adopted from [181]. The framework, chosen as a guide to find evidence for justifying the research questions, imposed the creation of theories based on models and propositions to be validated within a scope. The validation of the model was conducted as an on-line survey in three validation rounds, encompassing a growing number of participants. The survey was submitted to 134 experts of the field and on some public channels like relevant mailing lists and social networks. Its objective was to assess the model's readability, its level of coverage of the domain and its potential usefulness in the design of actual, derived systems. The questionnaires included quantitative Likert scale questions and free text inputs for comments. The development platform was validated in two scopes. As a small-scale experiment, the platform was used in a 12 hours training session where 4 developers had to perform an exercise consisting in developing a set of typical pHealth use cases At the end of the session, a focus group was held to identify benefits and drawbacks of the platform. The second validation was held as a test-case study in a large scale research project called HeartCycle the aim of which was to develop a closed-loop disease management system for heart failure and coronary heart disease patients [160]. During this project three applications were developed by a team of programmers and designers. One of these applications was tested in a clinical trial with actual patients. At the end of the project, the team was interviewed in a focus group to assess the role the platform had within the project. Results For what regards the model that describes the pHealth domain, its conceptual part includes a description of the main roles and concerns of pHealth stakeholders, a model of the ICT artefacts that are commonly adopted and a model representing the typical data that need to be formalized among pHealth systems. The functional model includes a set of 18 scenarios, divided into assisted person's view, caregiver's view, developer's view, technology and services providers' view and authority's view, and a set of 52 Use Cases grouped in 6 categories: assisted person's activities, system reactions, caregiver's activities, user engagement, developer's activities and deployer's activities. For what concerns the validation of the model, a total of 65 people participated in the online survey providing their level of agreement in all the assessed dimensions and a total of 248 comments on how to improve and complete the model. Participants' background spanned from engineering and software development (70%) to medical specialities (15%), with declared interest in the fields of eHealth (24%), mHealth (16%), Ambient Assisted Living (21%), Personalized Medicine (5%), Personal Health Systems (15%), Medical Informatics (10%) and Biomedical Engineering (8%) with an average of 7.25_4.99 years of experience in these fields. From the analysis of the answers it is possible to observe that the contacted experts considered the model easily readable (average of 1.89_0.79 being 1 the most favourable scoring and 5 the worst), sufficiently abstract (1.99_0.88) and formal (2.13_0.77) for its purpose, with a sufficient coverage of the domain (2.26_0.95), useful for describing the domain (2.02_0.7) and for generating more specific systems (2_0.75) and they reported a partial interest in using the model in their job (2.48_0.91). Thanks to their comments, the model was improved and enriched with concepts that were missing at the beginning, nonetheless it was not possible to prove an improvement among the iterations, due to the diversity of the participants in the three rounds. From the model, a development platform for the pHealth domain was generated called pHealth Patient Platform (pHPP). The platform includes a set of libraries, programming and deployment tools, a tutorial and a sample application. The main four modules of the architecture are: the Data Collection Engine, which allows abstracting sources of information like sensors or external services, mapping data to databases and ontologies, and allowing event-based interaction and filtering, the GUI Engine, which abstracts the user interface in a message-like interaction model, the Workow Engine, which allows programming the application's user interaction ows with graphical workows, and the Rule Engine, which gives developers a simple means for programming the application's logic in the form of \if-then" rules. After the 5 years experience of HeartCycle, partially programmed with pHPP, 5 developers were joined in a focus group to discuss the advantages and drawbacks of the platform. The view that emerged from the training course and the focus group was that the platform is well-suited to the needs of the engineers working in the field, it allowed the separation of concerns among the different specialities and it simplified some common development tasks like data management and asynchronous interaction. Nevertheless, some deficiencies were pointed out in terms of a lack of maturity of some technological choices, and for the absence of some domain-specific tools, e.g. for data processing or for health-related communication protocols. Within HeartCycle, the platform was used to develop part of the Guided Exercise system, a composition of ICT tools for the physical rehabilitation of patients who suffered from myocardial infarction. The system developed using the platform was tested in a randomized controlled clinical trial, in which 55 patients used the system for 21 weeks. The technical results of this trial showed that the system was stable and reliable. Some minor bugs were detected, but these were promptly corrected using the platform. This shows that the platform, as well as facilitating the development task, can be successfully used to produce reliable software. Conclusions The research work carried out in developing this thesis provides responses to the three three research questions that were the motivation for the work. RQ1 A model was developed representing the domain of personalised health systems, and the assessment of experts in the field was that it represents the domain accurately, with an appropriate balance between abstraction and detail. RQ2 A development platform based on the model was successfully developed. RQ3 The platform has been shown to assist developers create complex pHealth software. This was demonstrated within the scope of one large-scale project, but the generic approach adopted provides indications that it would offer benefits more widely. The results of these evaluations provide indications that both the model and the platform are good candidates for being a reference for future pHealth developments.

Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with Acquired Brain Injury

This paper presents the design, development and first evaluation of an algorithm, named Intelligent Therapy Assistant (ITA), which automatically selects, configures and schedules rehabilitation tasks for patients with cognitive impairments after an episode of Acquired Brain Injury. The ITA is integrated in "Guttmann, Neuro Personal Trainer" (GNPT), a cognitive tele-rehabilitation platform that provides neuropsychological services.

Modelo basado en técnicas de procesamiento de lenguaje natural para extraer y anotar información de publicaciones científicas

La rápida evolución experimentada en los últimos años por las tecnologías de Internet ha estimulado la proliferación de recursos software en varias disciplinas científicas, especialmente en bioinformática. En la mayoría de los casos, la tendencia actual es publicar dichos recursos como servicios accesibles libremente a través de Internet, utilizando tecnologías y patrones de diseño definidos para la implementación de Arquitecturas Orientadas a Servicios (SOA). La combinación simultánea de múltiples servicios dentro de un mismo flujo de trabajo abre la posibilidad de crear aplicaciones potencialmente más útiles y complejas. La integración de dichos servicios plantea grandes desafíos, tanto desde un punto de vista teórico como práctico, como por ejemplo, la localización y acceso a los recursos disponibles o la coordinación entre ellos. En esta tesis doctoral se aborda el problema de la identificación, localización, clasificación y acceso a los recursos informáticos disponibles en Internet. Con este fin, se ha definido un modelo genérico para la construcción de índices de recursos software con información extraída automáticamente de artículos de la literatura científica especializada en un área. Este modelo consta de seis fases que abarcan desde la selección de las fuentes de datos hasta el acceso a los índices creados, pasando por la identificación, extracción, clasificación y “curación” de la información relativa a los recursos. Para verificar la viabilidad, idoneidad y eficiencia del modelo propuesto, éste ha sido evaluado en dos dominios científicos diferentes—la BioInformática y la Informática Médica—dando lugar a dos índices de recursos denominados BioInformatics Resource Inventory (BIRI) y electronic-Medical Informatics Repository of Resources(e-MIR2) respectivamente. Los resultados obtenidos de estas aplicaciones son presentados a lo largo de la presente tesis doctoral y han dado lugar a varias publicaciones científicas en diferentes revistas JCR y congresos internacionales. El impacto potencial y la utilidad de esta tesis doctoral podrían resultar muy importantes teniendo en cuenta que, gracias a la generalidad del modelo propuesto, éste podría ser aplicado en cualquier disciplina científica. Algunas de las líneas de investigación futuras más relevantes derivadas de este trabajo son esbozadas al final en el último capítulo de este libro. ABSTRACT The rapid evolution experimented in the last years by the Internet technologies has stimulated the proliferation of heterogeneous software resources in most scientific disciplines, especially in the bioinformatics area. In most cases, current trends aim to publish those resources as services freely available over the Internet, using technologies and design patterns defined for the implementation of Service-Oriented Architectures (SOA). Simultaneous combination of various services into the same workflow opens the opportunity of creating more complex and useful applications. Integration of services raises great challenges, both from a theoretical to a practical point of view such as, for instance, the location and access to the available resources or the orchestration among them. This PhD thesis deals with the problem of identification, location, classification and access to informatics resources available over the Internet. On this regard, a general model has been defined for building indexes of software resources, with information extracted automatically from scientific articles from the literature specialized in the area. Such model consists of six phases ranging from the selection of data sources to the access to the indexes created, covering the identification, extraction, classification and curation of the information related to the software resources. To verify the viability, feasibility and efficiency of the proposed model, it has been evaluated in two different scientific domains—Bioinformatics and Medical Informatics—producing two resources indexes named BioInformatics Resources Inventory (BIRI) and electronic-Medical Informatics Repository of Resources (e-MIR2) respectively. The results and evaluation of those systems are presented along this PhD thesis, and they have produced different scientific publications in several JCR journals and international conferences. The potential impact and utility of this PhD thesis could be of great relevance considering that, thanks to the generality of the proposed model, it could be successfully extended to any scientific discipline. Some of the most relevant future research lines derived from this work are outlined at the end of this book.

Supporting patient screening to identify suitable clinical trials.

To support the efficient execution of post-genomic multi-centric clinical trials in breast cancer we propose a solution that streamlines the assessment of the eligibility of patients for available trials. The assessment of the eligibility of a patient for a trial requires evaluating whether each eligibility criterion is satisfied and is often a time consuming and manual task. The main focus in the literature has been on proposing different methods for modelling and formalizing the eligibility criteria. However the current adoption of these approaches in clinical care is limited. Less effort has been dedicated to the automatic matching of criteria to the patient data managed in clinical care. We address both aspects and propose a scalable, efficient and pragmatic patient screening solution enabling automatic evaluation of eligibility of patients for a relevant set of trials. This covers the flexible formalization of criteria and of other relevant trial metadata and the efficient management of these representations.

AMELIE: Authoring Multimedia-Enhanced Learning Interactive Environment for medical contents

This paper presents the AMELIE Authoring Tool for medical e-learning applications. The tool allows for the creation of enhanced-video based didactic contents, and can be adjusted to any number of platforms and applications. Validation provides preliminary good results on its acceptance and usefulness.

AMELIE: Authoring Multimedia-Enhanced Learning Interactive Environment for medical contents

This paper presents the AMELIE Authoring Tool for medical e-learning applications. The tool allows for the creation of enhanced-video based didactic contents, and can be adjusted to any number of platforms and applications. Validation provides preliminary good results on its acceptance and usefulness.

Accessing and managing open medical resources in Africa over the Internet

Recent commentaries have proposed the advantages of using open exchange of data and informatics resources for improving health-related policies and patient care in Africa. Yet, in many African regions, both private medical and public health information systems are still unaffordable. Open exchange over the social Web 2.0 could encourage more altruistic support of medical initiatives. We have carried out some experiments to demonstrate the feasibility of using this approach to disseminate open data and informatics resources in Africa. After the experiments we developed the AFRICA BUILD Portal, the first Social Network for African biomedical researchers. Through the AFRICA BUILD Portal users can access in a transparent way to several resources. Currently, over 600 researchers are using distributed and open resources through this platform committed to low connections.

Analysis of the suitability of existing medical ontologies for building a scalable semantic interoperability solution supporting multi-site collaboration in oncology

Semantic interoperability is essential to facilitate efficient collaboration in heterogeneous multi-site healthcare environments. The deployment of a semantic interoperability solution has the potential to enable a wide range of informatics supported applications in clinical care and research both within as ingle healthcare organization and in a network of organizations. At the same time, building and deploying a semantic interoperability solution may require significant effort to carryout data transformation and to harmonize the semantics of the information in the different systems. Our approach to semantic interoperability leverages existing healthcare standards and ontologies, focusing first on specific clinical domains and key applications, and gradually expanding the solution when needed. An important objective of this work is to create a semantic link between clinical research and care environments to enable applications such as streamlining the execution of multi-centric clinical trials, including the identification of eligible patients for the trials. This paper presents an analysis of the suitability of several widely-used medical ontologies in the clinical domain: SNOMED-CT, LOINC, MedDRA, to capture the semantics of the clinical trial eligibility criteria, of the clinical trial data (e.g., Clinical Report Forms), and of the corresponding patient record data that would enable the automatic identification of eligible patients. Next to the coverage provided by the ontologies we evaluate and compare the sizes of the sets of relevant concepts and their relative frequency to estimate the cost of data transformation, of building the necessary semantic mappings, and of extending the solution to new domains. This analysis shows that our approach is both feasible and scalable.