PubMed Health⌕ Search

Biomedical subjects

Vangelis Karkaletsis

Publications and source records attributed to Vangelis Karkaletsis.

6 recordsLinked to original sources
PubMed2006

Quality labelling of medical web content.

As the number of medical websites in various languages increases, it is increasingly necessary to establish specific criteria and control measures that give consumers some guarantee that the health websites they are visiting meet a minimum level of quality standards. Further, reassurance is needed that the professionals offering the information are suitably qualified. The paper briefly presents the current mechanisms for labelling medical web content and introduces the work done in the EC-funded project Quatro. This has defined a vocabulary for quality labels and a schema to deliver them in a machine-processable format. In addition, the paper proposes the development of a labelling platform that will assist the work of medical labelling agencies in automating, up to a certain level, the retrieval of unlabelled medical websites and their labelling, and the monitoring of labelled websites as to whether they are still satisfying the criteria.

Humans↗
PubMed2006

Overview: Computational analysis and decision support systems in oncology.

Computational analysis tools and decision support systems have increased their penetration in the support of clinical processes and management of medical data and knowledge. Applications range from adjunct tools for diagnosis and disease investigation to the treatment and monitoring of therapeutic procedures. As all medical fields, the field of oncology is affected. This special issue includes studies presenting research and applications of computational intelligence in oncology, covering four main areas: i) decision support systems (DSS) and artificial intelligence (AI) applications in oncology; ii) design and assessment of classification tools in oncology; iii) intelligent accessing, retrieving, and storing of medical images; and iv) intelligent telemedicine and telehealth applications in oncology.

Artificial Intelligence↗
PubMed2006

MedIEQ-Quality labelling of medical web content using multilingual information extraction.

Quality of Internet health information is essential because it has the potential to benefit or harm a large number of people and it is therefore essential to provide consumers with some tools to aid them in assessing the nature of the information they are accessing and how they should use it without jeopardizing their relationship with their doctor. Organizations around the world are working on establishing standards of quality in the accreditation of health-related web content. For the full success of these initiatives, they must be equipped with technologies that enable the automation of the rating process and allow the continuous monitoring of labelled web sites alerting the labelling agency. In this paper we describe the European project MedIEQ (Quality Labelling of Medical Web Content Using Multilingual Information Extraction) that integrates the efforts of relevant organizations on medical quality labelling, multilingual information retrieval and extraction and semantic resources, from six different European countries (Spain, Germany, Greece, Finland, Czech Republic and Switzerland). The main objectives of MedIEQ are: first, to develop a scheme for the quality labelling of medical web content and provide the tools supporting the creation, maintenance and access of labelling data according to this scheme and second, to specify a methodology for the content analysis of medical web sites according to the MedIEQ scheme and develop the tools that will implement it.

Accreditation↗
PubMed2005

Building an allergens ontology and maintaining it using machine learning techniques.

Ontologies are widely used for formalizing and organizing the knowledge of a particular domain of interest. This facilitates knowledge sharing and re-use by both people and systems. Ontologies are becoming increasingly important in the biomedical domain since they enable knowledge sharing in a formal, homogeneous and unambiguous way. Knowledge in a rapidly growing field such as biomedicine is usually evolving and therefore an ontology maintenance process is required to keep ontological knowledge up-to-date. This work presents our methodology for building a formally defined ontology, maintaining it exploiting machine learning techniques and domain specific corpora, and evaluating it using a well-defined experimental setting. The application of this methodology in the allergen domain is then discussed in detail presenting the ontology built, the specific techniques used and the evaluation settings.

Allergens↗
PubMed2005

Summarization from medical documents: a survey.

OBJECTIVE: The aim of this paper is to survey the recent work in medical documents summarization. BACKGROUND: During the last decade, documents summarization got increasing attention by the AI research community. More recently it also attracted the interest of the medical research community as well, due to the enormous growth of information that is available to the physicians and researchers in medicine, through the large and growing number of published journals, conference proceedings, medical sites and portals on the World Wide Web, electronic medical records, etc. METHODOLOGY: This survey gives first a general background on documents summarization, presenting the factors that summarization depends upon, discussing evaluation issues and describing briefly the various types of summarization techniques. It then examines the characteristics of the medical domain through the different types of medical documents. Finally, it presents and discusses the summarization techniques used so far in the medical domain, referring to the corresponding systems and their characteristics. DISCUSSION AND CONCLUSIONS: The paper discusses thoroughly the promising paths for future research in medical documents summarization. It mainly focuses on the issue of scaling to large collections of documents in various languages and from different media, on personalization issues, on portability to new sub-domains, and on the integration of summarization technology in practical applications.

Abstracting and Indexing↗