MammoApplet: an interactive Java applet tool for manual annotation in medical imaging

Web-based applications in computational medicine have become increasingly important during the last years. The rapid growth of the World Wide Web supposes a new paradigm in the telemedicine and eHealth areas in order to assist and enhance the prevention, diagnosis and treatment of patients. Furthermore, training of radiologists and management of medical databases are also becoming increasingly important issues in the field. In this paper, we present MammoApplet , an interactive Java applet interface designed as a web-based tool. It aims to facilitate the diagnosis of new mammographic cases by providing a set of image processing tools that allow a better visualization of the images, and a set of drawing tools, used to annotate the suspicious regions. Each annotation allows including the attributes considered by the experts when issuing the final diagnosis. The overall set of overlays is stored in a database as XML files associated with the original images. The final goal is to obtain a database of already diagnosed cases for training and enhancing the performance of novice radiologistsPeer ReviewedPostprint (author's final draft

Enhanced Search for Educational Resources - A Perspective and a Prototype from ccLearn

Users of search tools who seek educational materials on the Internet are typically presented with either a web-scale search (e.g., Google or Yahoo) or a specialized, site-specific tool. The specialized search tools often rely upon custom data fields, such as user-entered ratings, to provide additional value. As currently designed, these systems are generally too labor intensive to manage and scale up beyond a single site or set of resources.However, custom (or structured) data of some form is necessary if search outcomes foreducational materials are to be improved. For example, design criteria and evaluative metrics are crucial attributes for educational resources, and these currently require human labeling and verification. Thus, one challenge is to design a search tool that capitalizes on available structured data (also called metadata) but is not crippled if the data are missing. This information should be amenable to repurposing by anyone, which means that it must be archived in a manner that can be discovered and leveraged easily.In this paper, we describe the extent to which DiscoverEd, a prototype developed by ccLearn, meets the design challenge of a scalable, enhanced search platform for educational resources. We then explore some of the key challenges regarding enhanced search for topic-specific Internet resources generally. We conclude by illustrating some possible future developments and third-party enhancements to the DiscoverEd prototype

The Blogosphere at a Glance — Content-Based Structures Made Simple

A network representation based on a basic wordoverlap similarity measure between blogs is introduced. The simplicity of the representation renders it computationally tractable, transparent and insensitive to representation-dependent artifacts. Using Swedish blog data, we demonstrate that the representation, in spite of its simplicity, manages to capture important structural properties of the content in the blogosphere. First, blogs that treat similar subjects are organized in distinct network clusters. Second, the network is hierarchically organized as clusters in turn form higher-order clusters: a compound structure reminiscent of a blog taxonomy

Serving GODAE Data and Products to the Ocean Community

The Global Ocean Data Assimilation Experiment (GODAE [http:// www.godae.org]) has spanned a decade of rapid technological development. The ever-increasing volume and diversity of oceanographic data produced by in situ instruments, remote-sensing platforms, and computer simulations have driven the development of a number of innovative technologies that are essential for connecting scientists with the data that they need. This paper gives an overview of the technologies that have been developed and applied in the course of GODAE, which now provide users of oceanographic data with the capability to discover, evaluate, visualize, download, and analyze data from all over the world. The key to this capability is the ability to reduce the inherent complexity of oceanographic data by providing a consistent, harmonized view of the various data products. The challenges of data serving have been addressed over the last 10 years through the cooperative skills and energies of many individuals

A community based algorithm for deriving users' profiles from egocentrics networks: experiment on Facebook and DBLP

International audienceNowadays, social networks are more and more widely used as a solution for enriching users’ profiles in systems such as recommender systems or personalized systems. For an unknown user’s interest, the user’s social network can be a meaningful data source for deriving that interest. However, in the literature very few techniques are designed to meet this solution. Existing techniques usually focus on people individually selected in the user’s social network and strongly depend on each author’s objective. To improve these techniques, we propose using a community-based algorithm that is applied to a part of the user’s social network (egocentric network) and that derives a user social profile that can be reused for any purpose (e.g., personalization, recommendation). We compute weighted user’s interests from these communities by considering their semantics (interests related to communities) and their structural measures (e.g., centrality measures) in the egocentric network graph. A first experiment conducted in Facebook demonstrates the usefulness of this technique compared to individual-based techniques and the influence of structural measures (related to communities) on the quality of derived profiles. A second experiment on DBLP and the author’s social network Mendeley confirms the results obtained on Facebook and shows the influence of the density of egocentrics network on the quality of results

Data Mining in Electronic Commerce

Modern business is rushing toward e-commerce. If the transition is done properly, it enables better management, new services, lower transaction costs and better customer relations. Success depends on skilled information technologists, among whom are statisticians. This paper focuses on some of the contributions that statisticians are making to help change the business world, especially through the development and application of data mining methods. This is a very large area, and the topics we cover are chosen to avoid overlap with other papers in this special issue, as well as to respect the limitations of our expertise. Inevitably, electronic commerce has raised and is raising fresh research problems in a very wide range of statistical areas, and we try to emphasize those challenges.Comment: Published at http://dx.doi.org/10.1214/088342306000000204 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Collaborative Mapping of London Using Google Maps: The LondonProfiler

This paper begins by reviewing the ways in which the innovation of Google Maps has transformed our ability to reference and view geographically referenced data. We describe the ways in which the GMap Creator tool developed under the ESRC National Centre for E Social Science programme enables users to ‘mashup’ thematic choropleth maps using the Google API. We illustrate the application of GMap Creator using the example of www.londonprofiler.org, which makes it possible to view a range of health, education and other socioeconomic datasets against a backcloth of Google Maps data. Our conclusions address the ways in which Google Map mashups developed using GMap Creator facilitate online exploratory cartographic visualisation in a range of areas of policy concern

Freeing up access to learning: the role for Open Educational Resources

The internet revolution of the last few years has had an impact on how we all live our lives. So it is not surprising that this is also a time of change in attitudes towards how we learn. Free access to information through computer networks has expanded, and part of that information flow are materials designed to help people learn. In addition there are many further online resources that help the learning process, even if that was not the original aim. However, there are risks in this evolution in access to information both for the end user, who can be confused by the options available to them, and to those involved in providing education, who may see their traditional role changing and becoming harder to perform. This situation provides the background for a growing movement to directly consider how education can be provided in a freer and more open way. This has been termed “Open Educational Resources” (OER). The exact definition of the term depends on interpretation, however a useful statement was provided as an outcome from an event organized by UNESCO in 2002 as: “OER are teaching, learning, and research resources that reside in the public domain or have been released under an intellectual property license that permits their free use or re-purposing by others. Open educational resources include full courses, course materials, modules, textbooks, streaming videos, tests, software, and any other tools, materials, or techniques used to support access to knowledge (Atkins, Brown and Hammond, 2007, p4).” Arguably the only difference between an online learning object and an open educational resource is the declaration that it is open. This may be true but that turns out to be a powerful difference. By being open the content can be accessed by any learner who can do so, it can be taken and run in new contexts, it can be reworked by others and adapted for local needs (with the result shared back if desired), it can be made part of shared pool of resources, it can be the shared point of reference for collaboration, and it can be the key to building policies that work in different domain