26 research outputs found
Sign project telegenetics - providing remote genetic services in the cross-border region of Italy and Slovenia
This paper describes the telegenetics component of the SIGN project. Telegenetics is a subfield
of telemedicine applied to clinical genetics. In the SIGN project, telegenetics aims to provide remote genetic
services in the cross-border region of Italy and Slovenia. More specifically, the goal is to develop remote genetic
services in areas without them and to provide best expertise in clinical genetics without the need to travel
large distances (patients or professionals). The major telegenetics activities within the SIGN project are the
development of remote genetic services: for genetic counseling, for expert to expert communication, and for
communication between the partners of the project. To accomplish the activities, these major tasks had to
be done: testing and selection of video-conferencing equipment and software for secure data sharing and
exchange; development of work protocols; end-user education; installation, configuration and testing of
necessary hardware, software and developed protocols; and evaluation of user satisfaction (both patients
and genetic service providers). The preliminary evaluation results show promising user-satisfaction. They also
highlight areas where further improvement of the remote services is possible
Chi-square-based scoring function for categorization of MEDLINE citations
Objectives: Text categorization has been used in biomedical informatics for
identifying documents containing relevant topics of interest. We developed a
simple method that uses a chi-square-based scoring function to determine the
likelihood of MEDLINE citations containing genetic relevant topic. Methods: Our
procedure requires construction of a genetic and a nongenetic domain document
corpus. We used MeSH descriptors assigned to MEDLINE citations for this
categorization task. We compared frequencies of MeSH descriptors between two
corpora applying chi-square test. A MeSH descriptor was considered to be a
positive indicator if its relative observed frequency in the genetic domain
corpus was greater than its relative observed frequency in the nongenetic
domain corpus. The output of the proposed method is a list of scores for all
the citations, with the highest score given to those citations containing MeSH
descriptors typical for the genetic domain. Results: Validation was done on a
set of 734 manually annotated MEDLINE citations. It achieved predictive
accuracy of 0.87 with 0.69 recall and 0.64 precision. We evaluated the method
by comparing it to three machine learning algorithms (support vector machines,
decision trees, na\"ive Bayes). Although the differences were not statistically
significantly different, results showed that our chi-square scoring performs as
good as compared machine learning algorithms. Conclusions: We suggest that the
chi-square scoring is an effective solution to help categorize MEDLINE
citations. The algorithm is implemented in the BITOLA literature-based
discovery support system as a preprocessor for gene symbol disambiguation
process.Comment: 34 pages, 2 figure
Graph-Based Methods for Discovery Browsing with Semantic Predications
We present an extension to literature-based discovery that goes beyond making discoveries to a principled way of navigating through selected aspects of some biomedical domain. The method is a type of âdiscovery browsingâ that guides the user through the research literature on a specified phenomenon. Poorly understood relationships may be explored through novel points of view, and potentially interesting relationships need not be known ahead of time. In a process of âcooperative reciprocityâ the user iteratively focuses system output, thus controlling the large number of relationships often generated in literature-based discovery systems. The underlying technology exploits SemRep semantic predications represented as a graph of interconnected nodes (predication arguments) and edges (predicates). The system suggests paths in this graph, which represent chains of relationships. The methodology is illustrated with depressive disorder and focuses on the interaction of inflammation, circadian phenomena, and the neurotransmitter norepinephrine. Insight provided may contribute to enhanced understanding of the pathophysiology, treatment, and prevention of this disorder
DBKDA 2016 : the Eighth International Conference on Advances in Databases, Knowledge, and Data Applications : GraphSM 2016: the Third International Workshop on Large-Scale Graph Storage and Management : June 26 - 30, Lisbon, Portugal
The Eighth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2016), held between June 26 - 30, 2016 - Lisbon, Portugal, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and load-balancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the âde factoâ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology