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CORDIS

Knowledge Helper for Medical and Other Information users

Project description


Intelligent information management
Collect and make sense of biomedical information, then makes it freely and easily available in several languages

KHRESMOI aims to develop 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 language2. 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 information3. 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.

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 visualizationsThe 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 language2. 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 information3. Radiologists are drowning in images – at larger hospitals over 100GB (over 100000 images) are produced per dayRepresentative 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.

Call for proposal

FP7-ICT-2009-5
See other projects for this call

Coordinator Contact

Henning MÜLLER Mr.

Coordinator

HAUTE ECOLE SPECIALISEE DE SUISSE OCCIDENTALE
EU contribution
€ 1 715 660,00
Address
Route de Moutier 14
2800 Delemont
Switzerland

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Region
Schweiz/Suisse/Svizzera Espace Mittelland Jura
Activity type
Higher or Secondary Education Establishments
Administrative Contact
Alexandre Cotting (Mr.)
Links
Total cost
No data

Participants (12)