GAP Project - New Approach to Health Risk Prediction

The GAP Project's goal is to assess the need and the means for a "generic predictive model" for an ICT system capable to produce health alarms at EU level and design a roadmap for the future research on ICT tools for Guard (Detection), Anticipation and Prediction of potential large scale threats. The Project is focused on four types of risks: Biological (communicable diseases and bioterrorism), Natural, Industrial and Nuclear and Terrorist Risks.

The protection of the public's health is one of the most important aims of European countries. In the last decade, many efforts have been made to develop national and international systems for surveillance, anticipation and prediction of threats to public health, utilizing different tools for monitoring, data sharing and modeling. However, the overall technological design of systems that will be able to generate timely alerts and prediction of health threats, and the way to construct them, need still more development.

Investigation of aspects related to ICT research in new risk prediction, assessment and management tools for preparation, surveillance, support and intervention in case of largescale adverse health events was one of the main objectives of the European Commission, through the ICT e-health programme, when launching the GAP (Guard Anticipation & Prediction ) Project.

The GAP Project involves three major steps: Mapping "state of the art" technologies, outlining a generic ICT predictive model, and proposing a roadmap for the research needed to implement it.

The mapping exercise evidenced, among other findings, that there are significant differences between countries for both the processes and the information systems that they use to anticipate health threats; that most of the existing systems focus on surveillance and early detection rather than prediction; and, also, that systems are fragmented and do not function as an integrated structure.

The proposed generic model outlines the characteristics, from the technical and organizational point of view, of a future paneuropean structure, based on interoperability among the actual systems, serving as a tool for management and decision-making at the prediction level.

Currently, the GAP consortium, with the help of key experts, is finalizing the road map that includes the identified key ICT research activities proposed , in order to allow the development of future interoperable prediction systems.

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

Related article:

  • FP7 Projects: GAP

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...

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...

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...

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...