Med-e-Tel 2017 Call for Abstracts

Med-e-Tel 20175 - 7 April 2017, Luxembourg.
Join your colleagues from around the world to hear about and to see current telemedicine, telehealth and m/eHealth developments and to discuss collaboration opportunities at the 2017 edition of the Med-e-Tel conference, one of the annual events of the International Society for Telemedicine & eHealth.

Present your own research or experience with telemedicine, telehealth and m/eHealth services and applications! Submit your abstract via the Med-e-Tel website at www.medetel.eu/index.php?rub=educational_program&page=abstract_submission.

In a first stage, submission only takes a few minutes, you just need a short abstract (2200 characters max.). Once your abstract is accepted, you will be provided with information about paper submission and the submission of the actual presentation.

Deadline for abstract submission is December 4, 2016.

Some of the highlights of the Med-e-Tel 2017 conference program will include:

  • Quality Assessment of mHealth Apps
  • mHealth Apps Competition
  • Benchmarking the Quality of Telehealth Services
  • Teleconsultation and Virtual Visits
  • Artificial Intelligence, Big Data and Decision Support
  • Multidisciplinary Team Coordination in Oncology
  • Pharmacy and m/eHealth
  • Women and eHealth
  • Telecardiology

Submissions on additional relevant topics are welcome too.

For further information, please visit:
https://www.medetel.eu/?rub=educational_program&page=call_for_abstracts

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...