Complex challenges require interdisciplinary approaches. Find out at first hand which topics are of interest to experts. Be there when experienced physicians, engineers and computer scientists talk about future topics in radiology. And after the lectures, take advantage of the opportunity for networking and a lively exchange of opinions among nice colleagues.
Advances in healthcare and medical research are already strongly driven by information technology and engineering. Technologies like individual genome sequencing, high-performance multiparametric imaging or wearable medical devices generate exponentially growing datasets while contemporary data-mining techniques allow to extract large amounts of valuable data from existing archives of unstructured medical data. These offer the opportunity for highly specific clinical decision making and personalized precision medicine.
Further acceleration of medical innovation by upcoming technologies like artificial intelligence and smart hospital can be safely predicted. However, as complex challenges often require complex solutions, these technologies demand an interdisciplinary approach between clinicians, computer scientists, engineers, researchers, healthcare providers, legislators and many other disciplines.
We are poised to bring all stakeholders to the table to define the demands of clinicians and healthcare providers, outline technical solutions and create a common understanding of the opportunities, and also the difficulties that may arise. With the fourth ETIM meeting we aim to create new insights, stimulate networking and initiate a sustained flow of communication between individual experts and workgroups.
Chairman, Department of Radiology, Chief Medical Officer, IT department, University Hospital of Essen Dean of Research, Faculty of Medicine, University of Duisburg-Essen, Germany
Medical Director and Chief Executive Officer, University Hospital of Essen, Germany
AI Research, University Hospital of Essen, Department of Radiology, Germany
Chair for Computer Aided Medical Procedures & Augmented Reality,
Fakultät für Informatik, Technische Universität München
Consultant, Klinikum rechts der Isar,
Technical University of Munich, Munich, Germany
Digital Change Manager,
University Hospital Essen
Dean and Institute Director, FOM University, Essen, Germany
Radiologist, Head of Innovation Management, VISUS Health IT GmbH, Bochum, Germany
Medical Data and where to find it.
CEO, Therapixel, Paris, France
Can AI reach radiologists' performance in mammography screening?
AI Research, University Hospital of Essen, Germany
Yes we GAN: But sometimes we don’t even scan.
Resident Physician, Deutsches Krebsforschungszentrum, Heidelberg, Germany
Yes we GAN: But sometimes we don’t even scan.
Mathematics and Computer Science Division, Biology Division, Argonne National Laboratory, Argonne, USA
Data Science and Machine Learning for large scale Microbiome data.
Assistant Director Product Management, Biomax Informatics AG
Building Artificial Intelligence we can trust.
Head of Center for undiscovered and rare diseases (ZusE), University Hospital of Marburg, Germany
Certified Specialist Attorney for Medical Law,
Professor of Health and Social Legislation, IB Hochschule Berlin, Germany
You have to try the impossible to achieve the possible, (Hermann Hesse)
AI from the point of view of the lawyer
Head of Department Research & Analysis,
Services Department D&ICT,
University Hospital of Basel, Switzerland
AI in a clinical context; get ready to make your hands dirty!
Winner of the German National Youth Science Contest
„Jugend forscht“ for Mathematics/Informatics 2019,
Laureate of the European Union Contest for Young Scientists (EUCYS) 2019, Student
Neural Network application to key-point-detection in radiographs
Senior Researcher Inselspital,
University Hospital of Bern, Switzerland
Teach Medical Doctors how to train deep learning models
– a certificate of Advanced Study
Head of Institute at the
Sigmund Freud Private University Vienna, Austria
Psychological effects of artificial intelligenc and Big Data
Interventional Radiologist, Deep Learning / Medical AI Researcher,
West Palm Beach, Florida Area, USA
Moving from volume-based to outcomes-oriented healthcare:
What's the role of AI?
Head of Data Ideation & Service Innovation
Head of Business Project Managementy
Head of Business IT
NEXT Data Service AG
Integrated AI-driven OR-planning
Already Aristotle pointed out very early on the importance of community sense and networks.
For a few generations we see that political, private and business networks can be very successful.
Executive Director, Department of Physiology, University Hospital of Duisburg, Germany Dean for Studies and Teaching Faculty of Medicine, University of Duisburg-Essen, Germany
Head of Staff, Teaching with Media,
University Hospital Graz, Austria
Propositional MicroLearning and rapid content development
Senior Physician and Lecturer for Orthopaedics and Trauma Surgery,
Medical Director Curriculum Development
medical Competencies, Dean of Studies, University Hospital Essen, Germany
How it was, how it is and how it will be_An outline of forms of teaching
CEO, Co-Founder, knowledgefox.net
Mobile learing strategies for effective intergration of micro-learning in medical education
Head of teaching Medical Computer Science
University Medical Center Hamburg-Eppendorf (UKE),
E-Learning infrastructures for medical education:
Can we move from real to virtual
patients and hospital environments to allow more MicroLearning?
Managing Director, oddity evolve, Cologne, Germany
Effective developement in tailor-made learning worlds...visions or reality?
Executive Partner mmb Institut,
Adjunct Researcher DFKI, Education Technology Lab, Essen, Germany
MicroLearning - MicroCredits - MicroDegrees: New ways of education in medicine?
Head of Applications, Allm EMEA GmbH, Germany
Join - Medical Communication
Director, Infervision Europe Division, Germany
Build your own AI algorithm without coding, hype or reality?
CEO Lindera Germany
Decision Intelligence in healthcare: How does an AI learn medicine?
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