MEDNet

Access to medical care is sometimes very difficult to be reached from people living in rural and underserved areas. This problem is very well known in rural areas in Latin America. Citizens have no access to health care. They have to travel hundred of kilometres to receive a medical diagnosis.

MEDNet project will develop a medical network that addresses the problems of providing health care from a distance. The medical network will be supported by expert physician located in urban cities of Latin America. The medical applications will be vary from gynecology, pediatric, cardiology to typical infectious diseases for the region such as malaria and tuberculosis.

The examinations will involve ultrasound examination, ECG test and blood test and blood test imaging for automation diagnosis. All the patient information, extracted from the examinations will be stored a health care database, along with the demographic information and medication prescription. MedNET project will connect isolated region Amazon, in two different countries; Brazil, Peru Moreover MedNET will make use of AmerHis system (satellite communication) based on DVB-RCS.

MEDNet will make use of European standards for the communication and storage and medical data presentation.

The project will empower medical doctors to constantly and remotely keep track of their patients with minimum effort, assisted by an intelligent automated infrastructure. Furthermore, remote doctors will be able to share and request assistance form expert doctors located in urban cities. At the same time family and friends of the patients will also have access to the same information, filtered and presented in a comprehensible manner, including latest comments from the doctors. A sophisticated Collaboration Model will manage the whole service and will be aware of each patient's medical record, providing an information channel between the medical staff, the patients and their carers (family, friends, etc.).

For further information, please visit:
http://www.e-mednet.com

Project co-ordinator:
Fraunhofer Institute for Computer Graphics

Partners:

  • Thales Alenia Space España
  • Geopac
  • VICOMTech
  • MedCom GmbH
  • National Technical University of Athens
  • DIRESA Junin
  • Gobierno Regional de Junin
  • Servico National de Aprendizagem Industrial
  • Irmandade Da Santa casa de Misericordia de Porto Alegre
  • Hispasat S.A.

Timetable: from 01/2008 – to 12/2010

Total cost: € 2.177.440

EC funding: € 1.399.403

Programme Acronym: FP7-ICT

Subprogramme Area: Advanced ICT for risk assessment and patient safety

Contract type: Collaborative project (generic)


Related news article:

Most Popular Now

Most Advanced Artificial Touch for Brain…

For the first time ever, a complex sense of touch for individuals living with spinal cord injuries is a step closer to reality. A new study published in Science, paves...

Predicting the Progression of Autoimmune…

Autoimmune diseases, where the immune system mistakenly attacks the body's own healthy cells and tissues, often have a preclinical stage before diagnosis that’s characterized by mild symptoms or certain antibodies...

Major EU Project to Investigate Societal…

A new €3 million EU research project led by University College Dublin (UCD) Centre for Digital Policy will explore the benefits and risks of Artificial Intelligence (AI) from a societal...

Using AI to Uncover Hospital Patients�…

Across the United States, no hospital is the same. Equipment, staffing, technical capabilities, and patient populations can all differ. So, while the profiles developed for people with common conditions may...

New AI Tool Uses Routine Blood Tests to …

Doctors around the world may soon have access to a new tool that could better predict whether individual cancer patients will benefit from immune checkpoint inhibitors - a type of...

New Method Tracks the 'Learning Cur…

Introducing Annotatability - a powerful new framework to address a major challenge in biological research by examining how artificial neural networks learn to label genomic data. Genomic datasets often contain...

Picking the Right Doctor? AI could Help

Years ago, as she sat in waiting rooms, Maytal Saar-Tsechansky began to wonder how people chose a good doctor when they had no way of knowing a doctor's track record...

From Text to Structured Information Secu…

Artificial intelligence (AI) and above all large language models (LLMs), which also form the basis for ChatGPT, are increasingly in demand in hospitals. However, patient data must always be protected...

AI Innovation Unlocks Non-Surgical Way t…

Researchers have developed an artificial intelligence (AI) model to detect the spread of metastatic brain cancer using MRI scans, offering insights into patients’ cancer without aggressive surgery. The proof-of-concept study, co-led...

Deep Learning Model Helps Detect Lung Tu…

A new deep learning model shows promise in detecting and segmenting lung tumors, according to a study published in Radiology, a journal of the Radiological Society of North America (RSNA)...

New Study Reveals AI's Transformati…

Intensive care units (ICUs) face mounting pressure to effectively manage resources while delivering optimal patient care. Groundbreaking research published in the INFORMS journal Information Systems Research highlights how a novel...

One of the Largest Global Surveys of Soc…

As leaders gather for the World Economic Forum Annual Meeting 2025 in Davos, Leaps by Bayer, the impact investing arm of Bayer, and Boston Consulting Group (BCG) announced the launch...