NEUROWEB

NEUROWEB project improves healthcare delivery achieving knowledge-based, personalised diagnosis and therapy through vertical integration of existing clinical and genetic databases.NEUROWEB stimulates the sharing of knowledge on cerebrovascular diseases using an on-line web platform.

The amount of biomedical information that can be accessed through the Internet has reached a level no one could have dreamt of just ten years ago. The success of the genome sequencing projects has created an enormous amount of data that cannot be manually analysed. Since disease phenotypes arise from complex interaction between genetic factors and environment, the value of high-throughput genomic research would be dramatically enhanced by associations with key patient data. These data are generally available but of disparate quality and sources.The development of a data management system which integrates genomic databanks, clinical databases, and data mining tools embedded into a common resource accessible to health care professionals would be extremely advantageous.

Ischemic stroke is a major health problem in the developed countries. It is a complex, multigenic disorder, since there are several subtypes and risk factors, and most of the cases have non-mendelian inheritance. The integration and the analysis of a large number of well-defined clinical, radiological and molecular data will improve the evidence on the different roles played by genetic and environmental risk factors in stroke pathophysiology.

Within the framework of cerebrovascular disease, the objectives of the NEUROWEB project are:

  • To integrate clinical and genetic databases of the participating centres, different for structure and language, into a single virtual database;
  • To query the genetic databanks containing human genetic profiles present on the web;
  • To generate new knowledge on single patients with cerebrovascular disease, in order to achieve personalised prevention, diagnosis and therapy;
  • To promote collaborative research practices among the research communities involved in the project in order to share and enhance knowledge in the neurological domain.

The final aim of the NEUROWEB project is to foster vertical integration between clinical and genetic data in other common and complex diseases (i.e. cardiovascular diseases and tumours), in order to improve and personalise healthcare delivery in EC.

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

Project co-ordinator:
Istituto Nazionale Neurologico "Carlo Besta" (IT)

Partners:

  • Consiglio Nazionale delle Ricerche, Istituto di Tecnologie Biomediche (IT);
  • University of Milan – BICOCCA (IT)
  • Regione Lombardia (IT);
  • Erasmus University of Rotterdam (NL);
  • Medical School of Patras University (GR);
  • Orszagos Pszichiatriai es Neurologiai Intezet (HU);
  • University of Veszprém (HU);
  • SirseNet spa (IT);
  • Microsystems srl (IT);
  • Velti A.E. (GR)

Timetable: from 06/06 – to 05/08

Total cost: € 2.751.129

EC funding: € 1.883.500

Instrument: STREP

Project Identifier: IST-2006-518513

Source: FP6 eHealth Portfolio of Projects

Most Popular Now

ChatGPT can Produce Medical Record Notes…

The AI model ChatGPT can write administrative medical notes up to ten times faster than doctors without compromising quality. This is according to a new study conducted by researchers at...

Can Language Models Read the Genome? Thi…

The same class of artificial intelligence that made headlines coding software and passing the bar exam has learned to read a different kind of text - the genetic code. That code...

Bayer and Google Cloud to Accelerate Dev…

Bayer and Google Cloud announced a collaboration on the development of artificial intelligence (AI) solutions to support radiologists and ultimately better serve patients. As part of the collaboration, Bayer will...

Study Shows Human Medical Professionals …

When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations...

Shared Digital NHS Prescribing Record co…

Implementing a single shared digital prescribing record across the NHS in England could avoid nearly 1 million drug errors every year, stopping up to 16,000 fewer patients from being harmed...

Ask Chat GPT about Your Radiation Oncolo…

Cancer patients about to undergo radiation oncology treatment have lots of questions. Could ChatGPT be the best way to get answers? A new Northwestern Medicine study tested a specially designed ChatGPT...

North West Anglia Works with Clinisys to…

North West Anglia NHS Foundation Trust has replaced two, legacy laboratory information systems with a single instance of Clinisys WinPath. The trust, which serves a catchment of 800,000 patients in North...

Can AI Techniques Help Clinicians Assess…

Investigators have applied artificial intelligence (AI) techniques to gait analyses and medical records data to provide insights about individuals with leg fractures and aspects of their recovery. The study, published in...

AI Makes Retinal Imaging 100 Times Faste…

Researchers at the National Institutes of Health applied artificial intelligence (AI) to a technique that produces high-resolution images of cells in the eye. They report that with AI, imaging is...

SPARK TSL Acquires Sentean Group

SPARK TSL is acquiring Sentean Group, a Dutch company with a complementary background in hospital entertainment and communication, and bringing its Fusion Bedside platform for clinical and patient apps to...

Standing Up for Health Tech and SMEs: Sh…

AS the new chair of the health and social care council at techUK, Shane Tickell talked to Highland Marketing about his determination to support small and innovative companies, by having...

GPT-4 Matches Radiologists in Detecting …

Large language model GPT-4 matched the performance of radiologists in detecting errors in radiology reports, according to research published in Radiology, a journal of the Radiological Society of North America...