New FP7 eHealth Project - DebugIT

The DebugIT project is a large -scale integrating project funded within the 7th EU Framework Programme (FP7). The main objectives are to build IT tools that should have significant impacts for the monitoring and control of infectious diseases and antimicrobial resistances in Europe. This will be realized by building a technical and semantic infrastructure able to:
  • share heterogeneous clinical data sets from different hospitals in different countries, with different languages and legislations,
  • analyze large amounts of this clinical data with advanced multimedia data mining, and
  • apply the obtained knowledge for clinical decisions and outcome monitoring.

The DebugIT project, with its innovative approach, is an example of how ICT tools can be used to address the emerging challenges in healthcare. The DebugIT project addresses several of the overriding call topics at once by tackling the problems around antibiotics and of antimicrobial resistance of infectious diseases in an international consortium uniting world class research facilities, SMEs and industry partners.

It is an example of partnering at the European level to keep pace with soaring research costs by making use of complex IT technology technologies. It addresses the main socio-economic challenge in healthcare, namely to make Europe's healthcare systems safer and sustainable.

The research consortium includes public and private research institutions, university and teaching hospitals, industry and SMEs. The results of the application of the RTD will lead to higher patient safety and thereby fewer, more targeted intervention and fewer days in hospital. It means improving the overall productivity and efficiency of healthcare systems, delivering more personalised care solutions by allowing the actual patient data to be fed immediately into the system. It will therefore improving the Qquality of Life for patients and save their lives due to better, shorter and more targeted treatment. Patient safety is optimised through medical interventions with respect to treatment of infectious diseases and prescribing and administering antibiotics. The decision support will help avoid medical and other healthcare errors.

For further information, please visit:
http://www.debugit.eu

Related article:

Most Popular Now

AI Catches One-Third of Interval Breast …

An AI algorithm for breast cancer screening has potential to enhance the performance of digital breast tomosynthesis (DBT), reducing interval cancers by up to one-third, according to a study published...

Great plan: Now We need to Get Real abou…

The government's big plan for the 10 Year Health Plan for the NHS laid out a big role for delivery. However, the Highland Marketing advisory board felt the missing implementation...

Researchers Create 'Virtual Scienti…

There may be a new artificial intelligence-driven tool to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an...

From WebMD to AI Chatbots: How Innovatio…

A new research article published in the Journal of Participatory Medicine unveils how successive waves of digital technology innovation have empowered patients, fostering a more collaborative and responsive health care...

New AI Tool Accelerates mRNA-Based Treat…

A new artificial intelligence (AI) model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various...

AI also Assesses Dutch Mammograms Better…

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by...

RSNA AI Challenge Models can Independent…

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while...

AI could Help Emergency Rooms Predict Ad…

Artificial intelligence (AI) can help emergency department (ED) teams better anticipate which patients will need hospital admission, hours earlier than is currently possible, according to a multi-hospital study by the...

Head-to-Head Against AI, Pharmacy Studen…

Students pursuing a Doctor of Pharmacy degree routinely take - and pass - rigorous exams to prove competency in several areas. Can ChatGPT accurately answer the same questions? A new...

NHS Active 10 Walking Tracker Users are …

Users of the NHS Active 10 app, designed to encourage people to become more active, immediately increased their amount of brisk and non-brisk walking upon using the app, according to...

New AI Tool Illuminates "Dark Side…

Proteins sustain life as we know it, serving many important structural and functional roles throughout the body. But these large molecules have cast a long shadow over a smaller subclass...

Deep Learning-Based Model Enables Fast a…

Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for definitive diagnosis. However, conventional...