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Dive into the research topics where E.M. van Mulligen is active.

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Featured researches published by E.M. van Mulligen.


Bioinformatics | 2004

Distribution of information in biomedical abstracts and full-text publications

Martijn J. Schuemie; Marc Weeber; Bob J. A. Schijvenaars; E.M. van Mulligen; C C van der Eijk; Rob Jelier; Barend Mons; Jan A. Kors

MOTIVATION Full-text documents potentially hold more information than their abstracts, but require more resources for processing. We investigated the added value of full text over abstracts in terms of information content and occurrences of gene symbol--gene name combinations that can resolve gene-symbol ambiguity. RESULTS We analyzed a set of 3902 biomedical full-text articles. Different keyword measures indicate that information density is highest in abstracts, but that the information coverage in full texts is much greater than in abstracts. Analysis of five different standard sections of articles shows that the highest information coverage is located in the results section. Still, 30-40% of the information mentioned in each section is unique to that section. Only 30% of the gene symbols in the abstract are accompanied by their corresponding names, and a further 8% of the gene names are found in the full text. In the full text, only 18% of the gene symbols are accompanied by their gene names.


Bioinformatics | 2005

Co-occurrence based meta-analysis of scientific texts: retrieving biological relationships between genes

Rob Jelier; Guido Jenster; Lambert C. J. Dorssers; C C van der Eijk; E.M. van Mulligen; Barend Mons; Jan A. Kors

MOTIVATION The advent of high-throughput experiments in molecular biology creates a need for methods to efficiently extract and use information for large numbers of genes. Recently, the associative concept space (ACS) has been developed for the representation of information extracted from biomedical literature. The ACS is a Euclidean space in which thesaurus concepts are positioned and the distances between concepts indicates their relatedness. The ACS uses co-occurrence of concepts as a source of information. In this paper we evaluate how well the system can retrieve functionally related genes and we compare its performance with a simple gene co-occurrence method. RESULTS To assess the performance of the ACS we composed a test set of five groups of functionally related genes. With the ACS good scores were obtained for four of the five groups. When compared to the gene co-occurrence method, the ACS is capable of revealing more functional biological relations and can achieve results with less literature available per gene. Hierarchical clustering was performed on the ACS output, as a potential aid to users, and was found to provide useful clusters. Our results suggest that the algorithm can be of value for researchers studying large numbers of genes. AVAILABILITY The ACS program is available upon request from the authors.


Computer Methods and Programs in Biomedicine | 1993

A prototype integrated medical workstation environment

E.M. van Mulligen; T. Timmers; F. van den Heuvel; J. H. van Bemmel

In this paper the requirements, design, and implementation of a prototype integrated medical workstation environment are outlined. The aim of the workstation is to provide user-friendly, task-oriented support for clinicians, based on existing software and data. The prototype project has been started to investigate the technical possibilities of graphical user-interfaces, network technology, client-server approaches, and software encapsulation. Experience with the prototype encouraged discussion on both the limitations and the essential features for an integrated medical workstation.


computing in cardiology conference | 1990

HEARTVIEW-an object-oriented knowledge base to support clinical research in cardiology

B.deF. Leao; T. Timmers; J. van der Lei; E.M. van Mulligen

HEARTVIEW-a model to represent the data in a medical record-is presented. This model is based on the assumption that there is a general structure in the medical record. This general structure was modeled as a five-layered structure and implemented in an object-oriented environment. HEARTVIEW is an independent module of the medical workstation 2000 (MW2000), a project under development. The main goal of HEARTVIEW is to offer support for clinical research in cardiology. The description of the model and its implementation are presented.<<ETX>>


Annals of the Rheumatic Diseases | 2018

OP0113 Gradual tapering tnf blockers versus conventional synthetic dmards in patients with rheumatoid arthritis in sustained remission: first year results of the randomised controlled tara-study

E.M. van Mulligen; A. Weel; T.M. Kuijper; Jolanda J. Luime; Johanna M. W. Hazes; P.H.P. De Jong

Background Clinical and radiographic outcomes in rheumatoid arthritis (RA) have improved enormously in the last two decades, due to early detection of the disease, early initiation of ‘intensive’ therapy and a treat-to-target approach. As a result, 50%–60% of early RA patients will achieve sustained remission during the first year of follow-up. In aforementioned cases current guidelines recommend to consider tapering treatment, but an optimal approach to gradually de-escalate conventional synthetic or biologic DMARDs (respectively csDMARDs and bDMARDs) is currently lacking. Objectives The aim of this study is to evaluate the effectiveness of two tapering strategies, namely gradual tapering of csDMARDs and anti-TNF therapy during one year of follow-up.Abstract OP0113 – Figure 1 (A) Baseline characteristics and results after 12 months of follow-up of both tapering groups. (B) Cumulative flare over time, error bars indicate 95% confidence intervals


computing in cardiology conference | 1991

Knowledge-based modeling for the classification and follow-up of patients with congenital heart disease

F. van den Heuvel; E.M. van Mulligen; T. Timmers; John Hess

A model is presented for the support of clinical research in the domain of pediatric cardiology, in particular the long-term follow-up of patients with congenital heart disease (CongHD). It can be used for the collection, storage, retrieval, and analysis of data on a variety of hardware platforms. Using an object-oriented approach, a datamodel and an extensive controlled vocabulary of CongHd has been created. The model is part of the Medical Workstation 2000, an integrated graphical environment for the support of clinical research. The general structures of the model and of the vocabulary are described.<<ETX>>


computing in cardiology conference | 1990

CW2000: a medical workstation to support research in cardiology

E.M. van Mulligen; T. Timmers; A. Langhout; B.deF. Leao

The development of CW2000, an integrated workstation to support clinical research in cardiology is described. Four levels of integration are discussed: the levels of hardware, software, data and user-interface. The architecture of the system allows integration in a user-friendly shell of software packages currently in use for clinical research. The design and implementation of the workstation architecture are described. The workstation environment can be extended easily with other functions and the techniques for integration can be adapted for use in other clinical environments. The current status of the project, evaluation plans, and the trend for generalizing the concepts of integration are discussed.<<ETX>>


Methods of Information in Medicine | 1999

ORCA: the versatile CPR.

A.M. van Ginneken; H. Stam; E.M. van Mulligen; M. de Wilde; R. van Mastrigt; J. H. van Bemmel


Methods of Information in Medicine | 1993

A new architecture for integration of heterogeneous software components.

E.M. van Mulligen; T. Timmers; J. H. van Bemmel


Methods of Information in Medicine | 2002

Extensions to the HISA standard--the SynEx computing environment.

W. Grimson; B. Jung; E.M. van Mulligen; A.M. van Ginneken; S. Pardon; P. A. Sottile

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T. Timmers

Erasmus University Rotterdam

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J. H. van Bemmel

Erasmus University Rotterdam

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Barend Mons

Leiden University Medical Center

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Rob Jelier

Erasmus University Medical Center

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A.M. van Ginneken

Erasmus University Rotterdam

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Bob J. A. Schijvenaars

Erasmus University Medical Center

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C C van der Eijk

Erasmus University Rotterdam

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F. van den Heuvel

Erasmus University Rotterdam

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Jan A. Kors

Erasmus University Medical Center

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Marc Weeber

Erasmus University Rotterdam

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