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Cancer Informatics

Synopsis: An open access, peer reviewed electronic journal that covers the role of computational biology and bioinformatics in cancer treatment.


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About this journal

ISSN: 1176-9351



Aims and scope:

We live in a time when it is widely recognized that scientific collaborations across traditional disciplines can yield exponential gains through synergy. Cancer research is currently benefiting from advances in many fields, including biology (genomics and proteomics), physical chemistry (mass spectrometry and radio imaging), computer science and biostatistics (machine learning, artificial intelligence), and many others. Medical informatics is a field nearly as wide that includes patient information systems and related critical components of information management in the information age.

Bioinformatics and computational biology appear to play a central role at each nexus, in part because novel technologies lead to immense leaps in the amount and granularity of data from patients and patient samples.
 
The aim of Cancer Informatics is to provide open access to peer-reviewed high quality manuscripts reporting bioinformatic analysis of molecular genetic and/or clinical data pertaining to human cancer risk, prevention, outcome or treatment response.

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Submissions, excluding editorials, letters to the editor and dedications, will be peer reviewed by two reviewers.  Reviewers are required to provide fair, balanced and constructive reports.  

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Semantic Integration of Cervical Cancer Data Repositories to Facilitate Multicenter Association Studies: The ASSIST Approach

Authors: Theodoros Agorastos, Vassilis Koutkias, Manolis Falelakis, Irini Lekka, Themistoklis Mikos, Anastasios Delopoulos, Pericles A. Mitkas, Antonios Tantsis, Steven Weyers, Pascal Coorevits, Andreas M. Kaufmann, Roberto Kurzeja and Nicos Maglaveras
Publication Date: 03 Feb 2009
Cancer Informatics 2009:8 31-44

Theodoros Agorastos1, Vassilis Koutkias2, Manolis Falelakis3,4, Irini Lekka2, Themistoklis Mikos1, Anastasios Delopoulos3,4, Pericles A. Mitkas3,4, Antonios Tantsis1, Steven Weyers5, Pascal Coorevits6, Andreas M. Kaufmann7, Roberto Kurzeja7 and Nicos Maglaveras2

1Department of Obstetrics and Gynecology, Papageorgiou General Hospital, Aristotle University of Thessaloniki, Greece. 2Lab of Medical Informatics, Medical School, Aristotle University of Thessaloniki, Greece. 3Department of Electrical and Computer Engineering, Faculty of Engineering, Aristotle University of Thessaloniki, Greece. 4Informatics and Telematics Institute, Centre for Research and Technology Hellas, Greece. 5Department of Obstetrics and Gynecology, Faculty of Medicine and Health Sciences, Ghent University, Belgium. 6RAMIT vzw, c/o Department of Medical Informatics and Statistics, Ghent University Hospital, Ghent, Belgium. 7Gynäkologie, Charité-Universitätsmedizin Berlin, Germany.

Abstract

The current work addresses the unification of Electronic Health Records related to cervical cancer into a single medical knowledge source, in the context of the EU-funded ASSIST research project. The project aims to facilitate the research for cervical precancer and cancer through a system that virtually unifies multiple patient record repositories, physically located in different medical centers/hospitals, thus, increasing flexibility by allowing the formation of study groups “on demand” and by recycling patient records in new studies. To this end, ASSIST uses semantic technologies to translate all medical entities (such as patient examination results, history, habits, genetic profile) and represent them in a common form, encoded in the ASSIST Cervical Cancer Ontology. The current paper presents the knowledge elicitation approach followed, towards the definition and representation of the disease’s medical concepts and rules that constitute the basis for the ASSIST Cervical Cancer Ontology. The proposed approach constitutes a paradigm for semantic integration of heterogeneous clinical data that may be applicable to other biomedical application domains.

Categories: Bioinformatics , Cancer


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