Discussion of "Evidence-based health informatics:how do we know what we know?"

This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Evidence-based Health Informatics: How Do We Know What We Know?" written by Elske Ammenwerth [1]. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the Ammenwerth paper. In subsequent issues the discussion can continue through letters to the editor. With these comments on the paper "Evidence-based Health Informatics: How do we know what we know?", written by Elske Ammenwerth [1], the journal seeks to stimulate a broad discussion on the challenges of evaluating information processing and information technology in health care. An international group of experts has been invited by the editor of Methods to comment on this paper. Each of the invited commentaries forms one section of this paper.11 page(s

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

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

Nanoinformatics: developing new computing applications for nanomedicine

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others

Patient-Generated Health Data (PGHD) Interoperability:An Integrative Perspective

With advances in Digital Health (DH) tools, it has become much easier to collect, use, and share patient-generated health data (PGHD). This wealth of data could be efficiently used in monitoring and controlling chronic illnesses as well as predicting health outcome. Although integrating PGHD into clinical practice is currently in a promising stage, there are several technical challenges and usage barriers that hinder the full utilization of the PGHD potential in clinical care and research. This paper aims to address PGHD opportunities and challenges while developing the DH-Convener project to integrate PGHD into the Electronic Health Record in Austria (ELGA). Accordingly, it provides an integrative technical-clinical-user approach for developing a fully functional health ecosystem for exchanging integrated data among patients, healthcare providers, and researchers

Atanasijevic Andra levele Lukács Györgynek

En aquesta tesi s'estudia la metodologia numèrica de classificació de comunitats de vegetals. Les dades estudiades són inventaris de pastures dels estatges montà i subalpí, així com diversos matollars, màquies i boscos mediterranis. En un primer bloc de capítols s'aborden l'estructura i composició de les comunitats d'estudi. Concretament, s'estudia la diversitat de les comunitats i la suficiència de mostratge, la metodologia de càlcul de la fidelitat dels tàxons en bases de dades, i els problemes de discriminabilitat numèrica entre sintàxons. Un segon bloc d'aportacions s'ocupa d'estudiar pròpiament la metodologia de classificació: Es revisen i comparen diversos mètodes estadístics d'anàlisi de grups de vegetació (algoritmes jeràrquics aglomeratius, TWINSPAN, algoritmes partitius), s'estudia l'efecte que té la manera de mesurar les distàncies o proximitats entre inventaris sobre l'anàlisi de grups, es proposa un nou model de classificació per a l'anàlisi de grups de vegetació basat en l'algorisme Possibilistic C-means, i s'estudien estratègies de ponderació de variables (especies). El bloc final de capítols està dedicat a les aplicacions informàtiques desenvolupades. Per una banda es descriuen els programes QUERCUS, un editor de dades de vegetació, y GINKGO, una eina d'anàlisi multivariant basada en distàncies. Per l'altra, es presenta un sistema basat en el coneixement, anomenat ARAUCARIA, que té com a objectiu la determinació automàtica d'inventaris de vegetació.ENGLISHThis thesis studies the numerical classification methodology of plant community classification. The analyzed data sets are relevés from montane and subalpine grassland communities (O.Brometalia erecti), and mediterranean shrublands, maquis and forests (Cl. Quercetea ilicis). The first block of chapters approaches the structure and composition of the data sets. Concretely, community diversity and sampling sufficiency are studied first, followed by a chapter on taxon fidelity calculation methodology and another on numerical discriminability between syntaxa. The second block of chapters deals with numerical classification methodology itself: Cluster analysis numerical algorithms (hierarchical agglomerative, TWINSPAN, partitive) are reviewed and compared. The effect of numerical scalar transforms of data and proximity measures on clustering results are compared. A new vegetation data clustering strategy is proposed, on the basis of Possibilistic C-means algorithm. Finally, the effect of some variable weighting strategies on classification results are tested. The final chapters are devoted to describing software applications. On one hand two programs are described, the vegetation data editor QUERCUS and GINKGO, a multivariate analysis tool oriented to distance-based analyses. On the other hand, a knowledge-based system called ARAUCARIA is presented to provide automatic classification of relevé data