Open Call PHC-30-2015 Digital Representation of Health Data to Improve Disease Diagnosis and Treatment

European CommissionDigital personalised models, tools and standards with application for some specific clinical targets are currently available. There is however a need for greater integration of patient information, for example of multi-scale and multi-level physiological models with current and historical patient specific data and population specific data, to generate new clinical information for patient management. Any such integrative digital representation (Digital Patient) must also allow meaningful knowledge extraction and decision support.

Opening Date 30-07-2014
Publication date 11-12-2013 Deadline Date 21-04-2015 17:00:00 (Brussels local time)
Total Call Budget €104,500,000 Main Pillar Societal Challenges
Status Open OJ reference OJ C 361 of 11 December 2013

Proposals should focus on new decision support systems (DSS) based on a complex integration of heterogeneous data sources and subject-specific computer models. This should enable an integrated data analysis, and should present a highly visual data representation, using user-friendly interactive exploratory interfaces in order to assure usability and acceptability.

Proposals should enable the use of DSS by healthcare professionals for personalised prediction and decision in prevention, diagnosis or treatment and should take into account data protection and ethical considerations, as well as those pertaining to the inherent uncertainties and limits of prediction. The models should be already available, multi-level and multi-scale and will be integrated with the individual and population data relevant for the targeted clinical situations, e.g. the required molecular and cellular data, including genomics and epi-genomics, in vivo and in vitro imaging data, or data on administration of therapeutics and on nutrition/exposure to environmental factors and will be linked when relevant with computer models of personalised physiology, functional disorders and other diseases. The proposed systems should take advantage of the personal medical data accumulated over time. Proposals should include the standardisation of data formats. The integration of data coming from other new technologies for e.g. key-enabling technologies should be considered. Gender and ethical issues should be duly considered.

The Commission considers that proposals requesting a contribution from the EU of between EUR 3 and 5 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.

Expected impact:

  • Better coherent use of health data available for a subject in conjunction with the existing medical knowledge in clinical decision making
  • Design of predictive and therapeutic interventions
  • Better management of complex clinical situations.
  • Enabling use of the same information by different medical services and the other relevant healthcare professionals.
  • Better control and inter-service coordination in the management of the patient health.
  • Providing a consistent view of a patient's care needs.

Type of action: Research and innovation actions

For further information, documents and submission service, please visit:
http://ec.europa.eu/research/participants/portal/desktop/en/opportunities/h2020/topics/2273-phc-30-2015.html

Find your partners or consortia preparing a project proposal
If you need help to identify a potential partner or consortia with particular competences, facilities or experience, please join Health IT Space at http://www.healthitspace.eu

Health IT Space is the first social networking platform for Health IT Professionals and Stakeholders. Explore the list of all Health IT Space registered members at http://www.healthitspace.eu/network/members

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...

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...

The Human Touch of Doctors will Still be…

AI-based medicine will revolutionise care including for Alzheimer’s and diabetes, predicts a technology expert, but it must be accessible to all patients. Healing with Artificial Intelligence, written by technology expert Daniele...

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...

Brain Imaging may Identify Patients Like…

By understanding differences in how people’s brains are wired, clinicians may be able to predict who would benefit from a self-guided anxiety care app, according to a new analysis from...

Stepping for Digital Rewards

Walking is well known to have significant health benefits, but few people achieve the daily recommended steps. Fortunately, mobile health (mHealth) applications have emerged as promising tools to promote physical...