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Knowledge Helper for Medical and Other Information Users
01.05.2011 - 31.08.2014
Forschungsförderungsprojekt
In KHRESMOI, we will build a multi-lingual multi-modal search and access system for biomedical information and documents. This will be achieved by: - Effective automated information extraction from biomedical documents, including improvement using crowd sourcing and active learning, and automated estimation of the level of trust and target user expertise - Automated analysis and indexing for medical images in 2D (X-Rays), 3D (MRI, CT), and 4D (fMRI) - Linking information extracted from unstructured or semi-structured biomedical texts and images to structured information in knowledge bases - Support of cross-language search, including multi-lingual queries, and returning machine-translated pertinent excerpts - Adaptive user interfaces to assist in formulating queries and display search results via ergonomic and interactive visualizations The research will flow into several open source components, which will be integrated into an innovative open architecture for robust and scalable biomedical information search. The system will be evaluated in use cases by three well-defined user groups: 1. Members of the general public want access to reliable and understandable medical information in their own language 2. Clinicians and general practitioners need accurate answers rapidly ¿ a search on PubMed requires on average 30 minutes, while clinicians typically have 5 minutes available. Furthermore, over 40% of searches fail to provide relevant information 3. Radiologists are drowning in images ¿ at larger hospitals over 100GB (over 100000 images) are produced per day Representative groups of end users are available for sizable evaluations, accessed through a medical search engine with 11000 queries per day, a professional association of 2700 medical doctors, and two radiology departments with 175 radiologists. KHRESMOI is directed at Objective ICT-2009.4.3: Intelligent Information Management. It will focus on target outcome (a) capturing tractable information.
Personen
Projektleiter_in
Andreas Rauber
(E188)
Projektmitarbeiter_innen
Allan Hanbury
(E188)
Mihai Lupu
(E188)
Florina Piroi
(E188)
Matthias Samwald
(E188)
Veronika Stefanov
(E188)
Institut
E188 - Institute of Software Technology and Interactive Systems
Grant funds
European Commission (EU)
FP7 I.3 COOPERATION Information and Communication Technologies
7.Rahmenprogramm für Forschung
European Commission - Framework Programme
European Commission
Call identifier FP7-ICT-5
Application number 257528
Forschungsschwerpunkte
Computational Intelligence: 100%
Schlagwörter
Deutsch
Englisch
Informationssuche
Information Retrieval
medizinische Informatik
Medical Computer Science
Informationsextraktion
Information Extraction
Publikationen
Publikationsliste