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Platform for wide scale integration and visual representation of medical intelligence

Project description


eHealth
Better healthcare through improved diagnoses

The Greek word noesis means ‘the ability to sense or know something immediately’. That is a particularly handy trait for doctors, who often have to make spur-of-the-moment decisions. A new knowledge-management system will help them.

Developed by the NOESIS project, the knowledge-management system powers a decision-support framework for doctors to help them make diagnoses accurately and quickly, whether in an emergency ward or during routine treatment. It holds the promise of reducing the number of wrong diagnoses, leading to improved healthcare for patients.

In essence, it puts information at their fingertips whenever they need it and helps them use it effectively.

Helping diagnose heart diseases

The project partners have focused their work on assisting in the diagnosis of cardiovascular diseases, a segment of healthcare that is closely interlinked with many other medical complications. Indeed, the technology behind the system could be used in virtually any other medical field.

The NOESIS system allows doctors to rapidly access and analyse medical charts, sensor readings and scans while also providing them with recommendations on the best course of action in light of the unique medical situation of each patient.

It achieves this through a range of technologies that gather, store, sort and analyse medical information. The information can include written texts, graphs, images, audio and videos. The system can also be used in combination with databases containing electronic health records.

Efficient decision support

Thanks to data-mining techniques and semantic integration that associates medical concepts with information items, doctors can quickly retrieve the information they need from a hospital computer.

The decision-support component, meanwhile, can help them analyse that information to produce a preliminary diagnosis and even take preventive action.

Within the scope of the project, the system was used to support diagnoses of arrhythmia, ischemia and coronary heart disease, as well as to predict clinical restenosis in patients undergoing angioplasty with stenting.

Fewer medical errors

Such enhanced decision support has evident benefits for both doctors and patients.

Research has shown that experienced clinicians remember up to 2 million pieces of medical information and on average make 125 patient visits per week.

They face questions about diagnosis, prognosis and treatment, forcing them to make around 25 000 decisions each year. Studies have shown that up to 10% of those may have been wrong, of which about half were preventable mistakes.

With better knowledge management and decision support there would be less risk of doctors either giving the wrong diagnosis or prescribing an incorrect course of treatment. For patients, the system will result in a better quality of care.

NOESIS' objectives as an integrated project are twofold; Advancing research in the areasconcerned and increasing the exploitation potential of the produced system. The NOESIS projectaims at the development of a web-based personalised system with enhanced intelligence that willsupport health professionals in taking the best possible decision for prevention, diagnosis, andtreatment. The NOESIS system will assist health professionals in the diagnostic process, allowinga smooth transition from established medical knowledge to personal judgment through anenhanced site seer for medical sciences and a decision support framework capable of producing apreliminary diagnosis.The enhanced site seer will be based on a semantic integration platform associating medicalconcepts with information items, on a knowledge model for classification of extracted knowledgecomponents and on interactive multimodal and attentive interfaces. The semantic integration willassist intelligent agents to automatically reason about the information in the information retrievalprocess. Research will be conducted in several areas, including multimedia information retrievalbased on content similarity, classification algorithms based on hybrid methods combining fuzzyclustering and self organising maps (SOM), and dynamically generated distributed ontologies.On the other hand, the NOESIS system will put effort in research for generating an adaptableframework capable of reasoning about the patients' situation, producing a preliminary diagnosisand dealing with administered therapies. It will simulate the probabilistic reasoning that healthprofessionals implicitly perform, by producing qualitative and quantitative models representingdeterministic causal relationships and probabilistic associations between symptoms and diseases.The project will conclude with extensive testing and evaluation of the system by medical expertsand demonstration to well text truncated for the purposes of the ESR

Fields of science

Programme(s)

Topic(s)

Call for proposal

FP6-2002-IST-1
See other projects for this call

Funding Scheme

IP - Integrated Project

Coordinator

BOEHRINGER INGELHEIM ITALIA - S.P.A.
EU contribution
€ 896 060,10
Address
LOCALITA PRULLI 103/C
50066 REGGELLO
Italy

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Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
No data

Participants (13)

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Last update: 5 April 2023

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Permalink: https://cordis.europa.eu/project/id/507960

European Union, 2024