ARTEMIS

ARTEMIS develops a semantic web services based interoperability framework for the health care domain. This project provides the healthcare industry with an ideal platform to exchange meaningful clinical information among healthcare institutes through semantic mediation.

One of the key problems in healthcare informatics is the inability to share patient records across enterprises. There are several standardization efforts to digitally represent clinical data such as HL7 CDA, EHRcom and openEHR. These EHR standards, which are currently under development, aim to structure and mark-up the clinical content for the purpose of exchange.

However, since there are more than one standard, it is still difficult to achieve interoperability and today the clinical data is mostly stored in proprietary formats. ARTEMIS message exchange framework is developed to provide the exchange of meaningful clinical information among healthcare institutes through semantic mediation.The framework involves first providing the mapping of source ontology into target message ontology.

This mapping is used to automatically transform the source ontology message instances into target message instances. The framework proposed is generic enough to mediate between any incompatible healthcare standards that are currently in use.

For further information, please visit:
http://www.srdc.metu.edu.tr/webpage/projects/artemis/

Project co-ordinator:
Middle East Technical University - Software R&D Center

Partners:

  • Software R&D Center, Middle East Technical University , METUSRDC, (TR)
  • Kuratorium Offis E.V., OFFIS (DE)
  • South and East Belfast Health and Social Services Trust, SEBT, (UK)
  • Altec Information and Communications Systems S.A., ALTEC (GR)
  • Tepe Teknolojik Servisler AS,Tepe Technology (TR)
  • IT Innovation Center, Southampton University, IT Innovation (UK)

Timetable: from 01/04 - to 06/06

Total cost: € 2.957.604

EC funding: € 1.989.000

Instrument: STREP

Project Identifier: IST-2002-002103

Most Popular Now

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...

AI, Health, and Health Care Today and To…

Artificial intelligence (AI) carries promise and uncertainty for clinicians, patients, and health systems. This JAMA Summit Report presents expert perspectives on the opportunities, risks, and challenges of AI in health...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...

New AI Tool Makes Medical Imaging Proces…

When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is...