Vermutlich – vorausgesetzt, wir füttern sie mit den passenden Algorithmen und Daten. Denn sie kombinieren das Wissen von vielen Ärzten. Die Mediziner von morgen werden nicht mehr allein entscheiden müssen, sondern erhalten Unterstützung. So wird es eine Vernetzung zwischen vielen Disziplinen geben, etwa mit Computerexperten, Statistikern und Genetikern.
Continue reading (German version only) in the release of Freie Presse or Sächsische Zeitung.
Today, Prof. Wanka — head of the German Federal Ministry of Education and Research — announced the HiGHmed Medical Informatics Consortium as funded project consortium in the BMBF Federal Medical Informatics Initiative. Together with the three consortia DIFUTURE, SMITH, and MIRACUM, we are looking forward to sharpen the vision of a digital healthcare system in Germany in the upcoming years.
We are happy to contribute to the “Plattform Life Sciences” issue March 2017 focusing on the digital transformation within the life sciences. In our contribution, we share latest details about our data donation pass for citizens. With its help, citizens get full access to their personal healthcare data so they can request and aggregate them from individual participants in the healthcare system and donate them for individual purposes. Thus, citizens are able to perform their right on information self-determination for the first time in an extensive way.
The slide deck of the presentation “When time matters” of the workshop “The Genomics Revolution: from navigating NGS technologies to real time analysis & integration of big bio data” on Jan 31, 2017 in London is online available now.
We are happy to contribute to the “Management & Krankenhaus” issue Sep 2016. In our contribution, we introduce a data donation pass for patients. With the personal data donation pass, patients get fill access to their personal medical data so they can request and aggregate their data from individual participants in the healthcare system. Furthermore, patients get full control to manage access to their data, e.g. to share a de-identified subset of their data for a specific research project.