Clinical AI Conference &
Datathon Munich
May 15th - 17th 2019

Clinical Artificial Intelligence Conference & Datathon

Clinical AI Conference & Datathon aims to foster collaboration between physicians and data scientists to improve patient care. Participants will deepen their understanding and skills of the extraction of clinically relevant knowledge form data during the conference keynote talks and hands-on workshops. They further have the opportunity to work on a challenging case study during the datathon running in parallel to the conference.

Mankind has always been fascinated by the idea of creating technology that would match or even supersede human intelligence. While artificial intelligence after its birth in Dartmouth in 1956 had a rather slow start in medicine, new computational technologies and data acquisition, storage and analytic methods have arisen to allow the utilization of knowledge from millions of clinicians encoded in large clinical repositories. However, extracting this knowledge and translating it into clinical practice is a complex task, strewn with pitfalls. To identify and overcome these obstacles, international community efforts are required, combining the strengths of the knowledge of clinicians and data scientists. Therefore it is our mission to bring people together, combine strengths of these individual disciplines to achieve better patient care.

What is a Datathon

A Datathon in medicine is a format, where interdisciplinary teams work with a database or dataset to answer medically relevant questions. In our Datathon, we will provide a dataset extracted from the MIMIC III Intensive Care database.

This format has recently gained great attention in the medical domain. Its interactive nature brings together various groups, such as medical professionals, data scientists, informaticians, epidemiologists, and healthcare industrialists. Hence, it enables highly efficient utilization of the enormous amounts of health data available these days.

Different teams will work on the same dataset and results will be compared at the end of the conference. This is a great chance for medical professionals to get involved with and learn about methods and possibilities of statistics and machine learning, and for informatics, statisticians, and epidemiologists to learn about medicine.

You Should Register

If you are

  • a clinician, who is curious about how AI can and will affect your daily routine,
  • a coder, who is fascinated by the infinite possibilities the medical world has to offer,
  • a data scientist, who is passionate about discovering unknown correlations and causations in medical Big Data,
  • a nurse, a student, or a professional working in the medical/pharmaceutical field who wants to contribute to new developments in medical AI.

Of course we also would love to hear about your creative ideas if you are excited about meeting people from different fields that share your interest, looking for collaboration partners or always wanted to come to Munich.

Don't hesitate to register.
If you require further information, just contact us


Show on Google Maps

LMU Klinikum der Universitaet Muenchen
Hospital of the Ludwig-Maximilians-University (LMU) Munich
Campus Großhadern
Marchioninistr. 15
81377 Munich, Bavaria, Germany

Follow signs to 'Hörsäle' (lecture halls)

Conference Schedule

The conference will start on Wednesday, May 15th morning and last until Friday 17th afternoon. While the final program is still subject to change, Wednesday morning the datathon will start, teams will be assigned, the research question discussed and the dataset presented. Thursday will focus on scientific talks, presentation of methods of artificial intelligence and their applications, while the data athletes have time to work on the data extraction and analysis in the afternoon. Friday is designated to talks regarding the perspective of AI in medicine. Datathon teams will present their results.

Wednesday - May 15 2019
+ Opening Ceremony Datathon 09:00 10:00 Lecture Hall VII
Official start of the Datathon: Introduction to the dataset and the problem(s) to be analyzed. Registration will start at 8:00 a.m.
Time: 09:00 - 10:00
Location: Lecture Hall VII
Welcome and Introduction
Allocation of Datathon Teams
Presentation of the Dataset
Coffee Break
+ Datathon I 10:00 12:30 Lecture Hall Zeus
Time for the datathon teams to work on the problem - Mentors will support the teams
Time: 10:00 - 12:30
Location: Lecture Hall Zeus
Lunch Break
+ Opening Ceremony Conference 13:30 15:00 Lecture Hall VII
Conference Registration will start at 12:30.
Time: 13:30 - 15:00
Location: Lecture Hall VII
Therapeutic Decisions and Machine Learning
Artificial Intelligence in Anesthesia, Intensive Care and Emergency Medicine
The Medical AI Bubble will burst unless...
Coffee Break
+ Datathon II 15:15 17:30 Lecture Hall Zeus
Part two of the Datathon
Time: 15:15 - 17:30
Location: Lecture Hall Zeus
Basics of Medical Informatics for Clinicians
Django and MIMIC - a great marriage
Social Event
A Datathon in medicine is a format, where interdisciplinary teams work with a database or dataset to answer medically relevant questions. In our Datathon, we will provide a dataset extracted from the MIMIC III Intensive Care database to figure out the optimal potassium levels for patients during Intensive Care treatment. The entire ICU stay for patients was segmented into 2 hour chunks. For each given time window information on serum potassium, antiarrhythmic medication, vasopressors, diuretics, SOFA score, etc. will be given.

Different teams will work on the same dataset and results will be compared at the end of the conference. This is a great chance for medical professionals to get involved with and learn about methods and possibilities of statistics and machine learning, and for informatics, statisticians, and epidemiologists to learn about medicine.
Thursday - May 16 2019
+ Machine Learning in Medicine I 09:00 10:30 Lecture Hall VII
Machine learning has already impacted our lives on many different levels. In this session, perspectives and ideas on machine learning in medicine will be explored.
Time: 09:00 - 10:30
Location: Lecture Hall VII
Estimation of Personalized Treatment Effects
AI in Neurosurgery
AI in Nursing Informatics
Coffee Break
+ Machine Learning in Medicine II 10:45 12:15 Lecture Hall VII
Machine learning has already impacted our lives on many different levels. In this session, perspectives and ideas on machine learning in medicine will be explored.
Time: 10:45 - 12:15
Location: Lecture Hall VII
Clinical Validation of Machine Learning Models
Data Analytics with Cerebral Oximetry
Probabilistic approaches to solving the inverse problem of state and parameter estimation for mechanistic models of physiology: from theory to practice
Lunch Break
+ International ... 13:00 14:30 Lecture Hall VII
In order to make the most of modern AI technology, it is of utmost importance to work together. In this session, current efforts around the globe will be discussed.
Time: 13:00 - 14:30
Location: Lecture Hall VII
AI in the times of the GDPR
AI - only for those who can afford it?
Celi, Ohno-Machado, Mansmann
Panel Discussion
Coffee Break
+ ... and National 14:45 16:15 Lecture Hall VII
In order to make the most of modern AI technology, it is of utmost importance to work together. In this session, current efforts in Germany will be discussed.
Time: 14:45 - 16:15
Location: Lecture Hall VII
DIFUTURE - Data Integration for Future Medicine
AI and the Perioperative Course
Driving IT Innovations in Healthcare
Coffee Break
+ Workshops 16:30 18:00 announcement
Workshops provide a great way to dive deeper into the methodology of data analysis.
Time: 16:30 - 18:00
Location: announcement
A Whirlwind Tour Through Clinical Machine Learning
From Ideation to Entrepreneurship: The Role of Artificial Intelligence in Healthcare Innovation
+ Datathon III 16:30 18:00 Lecture Hall Zeus
The final part of the datathon
Time: 16:30 - 18:00
Location: Lecture Hall Zeus
Friday - May 17 2019
+ Perspectives 09:00 11:30 Lecture Hall VII
Where will artificial intelligence - and especially machine learning - lead medicine? What are the challenges and obstacles?
Time: 09:00 - 11:30
Location: Lecture Hall VII
Data, AI & Co. How MeDIC empowers the future of medicine.
Big Data versus Personalized Medicine - Really a Contradiction?
Clinical Use Cases
The Ethical Oversight of Clinical AI
The Value of AI in Nutritional Research
Collaborate to Innovate - A European Perspective
Coffee Break
+ Presentations from the Datathon 12:00 13:30 Lecture Hall VII
The datathon athletes will present their results for given research questions relevant to medicine. Based on the answers.
Time: 12:00 - 13:30
Location: Lecture Hall VII


Registration is closed.

Data Privacy Agreement

Privacy and confidential treatment of your information is very important to us. By registering for this conference you agree to having read, understood, and consent to the storage and use of your data.

This website uses cookies, for example to ensure security (such as CSRF protection). All information you provide for registration is voluntary. Online registration is necessary, however, to register for the conference and/or the datathon. Your eMail address will be used to contact you with payment information following registration and might be used to contact you before or after the datathon in order to

  • contact you with updated information
  • contact you after the datathon to make you aware of and allow you to access content relevant to the datathon.

During registration, we will also ask your permission to contact you for upcoming datathons. Information about your professional background will be important to us to optimize the content of the conference. Since this is an international conference, we are interested in finding out, where registrants come from. All information is stored in a secured and password-protected database not accessible from the internet. Analyses of the distributions of professional background or country of residence will be performed in an anonymized manner, i.e. without name information. IP addresses are not tracked and only stored intermediary in the webserver's logfiles, which are regularly deleted.

Pricing Information

Individual Pricing Information upon Request


If you want to get in personal contact with us, you can send a contact request with a short message using the following form. Please remember to include all relevant information.

I have read and accept the data privacy agreement

Leo Celi

Leo Anthony Celi has practiced medicine in three continents, giving him broad perspectives in healthcare delivery. As clinical research director and principal research scientist at the MIT Laboratory for Computational Physiology (LCP), and as an attending physician at the Beth Israel Deaconess Medical Center (BIDMC), he brings together clinicians and data scientists to support research using data routinely collected in the process of care. His group built and maintains the public-access Medical Information Mart for Intensive Care (MIMIC) database, which holds clinical data from over 60,000 stays in BIDMC intensive care units (ICU). He is one of the course directors for HST.936 – global health informatics to improve quality of care, and HST.953 – collaborative data science in medicine, both at MIT. He is an editor of the textbook for each course, both released under an open access license. The massive open online course HST.936x “Global Health Informatics to Improve Quality of Care” was launched under edX in February 2017. Finally, Leo has spoken in more than 30 countries about the value of data in improving health outcomes.

Lucila Ohno-Machado

Lucila Ohno-Machado is Full Professor and Chair of the Department of Biomedical Informatics, as well as Associate Dean for Informatics and Technology at University of California, San Diego. She serves as the Director for the Biomedical Research Informatics for Global Health Program as well as the San Diego Biomedical Informatics Education and Research Program. Furthermore, she served for eight years as the Editor-in-Chief of the Journal of the American Medical Informatics Association (JAMIA). Amongst her many accomplishments, her recent efforts have focused on creating and advancing iDASH - integrating Data for Analysis, Anonymization, and Sharing. iDASH stands for the development of technology that allows data sharing and utilization in a privacy preserving manner.

Maurizio Cecconi

Maurizio Cecconi is Full Professor of Anesthesia and Intensive Care Medicine at Humanitas University and the Head of Department at the Humanitas Research Center in Milan. He previously worked as Reader and Clinical Director at the Adult Critical Care Department of St George's Hospital and University of London. He has been very active in clinical research in Intensive Care, Anesthesia, Perioperative and Emergency Medicine, focusing on hemodynamic monitoring and optimisation, physiology of the critically ill patient, and epidemiology of perioperative outcomes. He served as Chair of Scientific Affairs of the European Society of Intensive Care Medicine and has recently been appointed President-elect for 2020-2021. He hosted ESICM's Big Data Talk & Critical Care Datathon in Milan in February 2019.

Djillali Annane

Djillali Annane is the Counselor of the French Minister of Health for Research and Medical Education and Dean of the Faculty of Medicine at the University of Versailles SQY, was the President of the Council of Deans of the Paris Universities, was the Vice-Chancellor of university of Versailles from 2004 to 2007, and is the President of the French Society of Intensive Care Medicine, and the Head of the critical care department at Raymond Poincaré University Hospital (AP-HP) in Garches, Paris, France. He has completed MD in 1991, and a PhD in pharmacology in 1995, both at Paris Descartes University. He has contributed to the medical literature with more than 260 peer-reviewed articles, has written about 100 book chapters, has given more than three hundred invited conferences at international scientific meeting, and has been invited as a visiting professor in numerous academic centers in Europe, North America and Australia (source:

Herwig Gerlach

Herwig Gerlach is the Director of the Department of Anesthesiology, Critical Care, and Pain Management at the Vivantes Klinikum Neukoelln Hospital in Berlin, Germany. His expertise spans from cellular mechanisms of pathogenesis of inflammation and sepsis over strategies on bedside laboratory monitoring of inflammatory mediators in patients with severe sepsis, and multiple trauma to Medical Informatics.In his Master thesis for the MBA, which was finished in 2014, he analyzed more than 6,000 calls for pre-hospital emergency units and found several associations of patient-dependent and independent impact factors for the quality of care. The last years, Dr. Gerlach concentrated on the implementation of Markov simulation methods for predictive modeling in critically ill patients based on large data bases from international studies. At present, he is leading the Vivantes group hospitals as participant of the German ICOSMOS project, which is a government-sponsored quality improvement program for severe sepsis. He was Chair of the ESICM Section “Systemic Inflammation and Sepsis”, constituted the Steering Committee of the Sepsis Survival Campaign and is currently Vice President of the German Sepsis Society.

Marine Flechet

Marine Flechet holds a PhD in Biomedical Sciences from the University of Leuven, Belgium. In her PhD, she developed prediction models for acute kidney injury and traumatic brain injury in critical illness, and translated these models into bedside clinical applications. She received her Master's degree in Biomedical Engineering from the University of Liège, Belgium, and the École Polytechnique Fédérale de Lausanne, Switzerland. Her work on the application of artificial intelligence for glucose control in intensive care, in collaboration with the University of Canterbury, New Zealand, was awarded twice the prize of the best master’s thesis in (Biomedical) Engineering (AILg and AIM).

Sven Zenker

Sven Zenker is an attending physician in the Department of Anesthesiology and Intensive Care Medicine at the University Clinic in Bonn. He has additional expertise in mathematics, physics, and computer science.

Nidan Qiao

Dr. Nidan Qiao is a neurosurgeon at Huashan Hospital, Fudan University. His research work is centered on integrating innovative statistical approaches to neurosurgical and neuroendocrine diseases. His main projects were visual prognosis in patients with pituitary adenomas, endocrine prognosis in patients with sellar region tumors and machine learning application in clinical medicine. He is the author or co-author of more than 25 peer-reviewed publications in Neurosurgery and Endocrinology and a regular peer-reviewer for many professional Journals. He will publish a book on deep learning in 2019. He recieved several domestic and interantional research funds on artificial intelligence. He had several oral presentations at different international conferences on both neurosurgery and artificial intelligence. He got fellowship award from MILSTEIN MEDICAL ASIAN AMERICAN Partnership Foundation. Dr. Qiao received his M.D. in Clinical Medicine from Fudan University. He is now in Master of Medical Science in Clinical Investigation program at Harvard Medical School and doing clinical research in Massachusettes General Hospital.

Delwin Villarante

Delwin Villarante MSHI, BSN, RN, CTFL is an informaticist and certified software quality assurance test engineer at Philips Healthcare in the Patient Care Monitoring and Analytics business group. Prior to joining Philips, he worked full time as a critical care RN at Beth Israel Deaconess Medical Center in Boston where he continues to practice on a per diem basis. Delwin has been a clinician for over 17 years. His clinical experience ranges from long term care to acute, critical care and emergency services. His industry background includes a role as a clinical specialist for Transmedics Inc, where he traveled around the US and Germany supporting clinical trial of the Organ Care System. He was also a clinical informatics analyst for New England Baptist Hospital. He obtained his BS in Nursing at The Pontifical and Royal University of Santo Tomas in España Manila, and received his MS in Health Informatics degree at Northeastern University in 2014. He currently serves as Director for membership and recruitment at NENIC (New England Nursing Informatics Consortium), and is currently exploring a multi-disciplinary study on burnout among critical care nurses.

Raffael Bild

Raffael Bild is an informaticist and one of the technical innovators of the DIFUTURE project. He is a specialist on a variety of research topics with a focus on differential private processing of biomedical data.

Heidi Seibold

Heidi Seibold is a statistician who is passionate about open and reproducible research. She develops machine learning methods for personalized medicine. Her methodological work is in the conjunction of statistics and machine learning and her focus is on tree and random forest methods in combination with regression models.

Bettina Jungwirth

Prof. Dr. Bettina Jungwirth is a full professor at the Department of Anesthesiology and Intensive Care Medicine of the Technical University of Munich. As head of the division of perioperative medicine she established a research group of Big Data and Artificial Intelligence in this field. Recently she obtained two grants to develop (1) a decision support tool for preoperative assessment and (2) a real time perioperative risk calculator for postoperative complications.

Stuart McLennan

Stuart McLennan is a Senior Research Associate at the Technical University of Munich's Institute of History and Ethics in Medicine, and a Postdoctoral Researcher at the University of Basel's Institute for Biomedical Ethics. He is a member of the editorial board of BMC Health Services Research as an Associate Editor. He is also a member of the Deutsches Netzwerk Evidenzbasierte Medizin e.V. [German Network for Evidence-based Medicine] and the Akademie für Ethik in der Medizin e. V. [German Academy for Ethics in Medicine]. He an interdisciplinary bioethicist; integrating ethical, legal, and policy analysis with empirical methodologies (quantitative/qualitative). He has recognized expertise regarding ethical, legal, and policy analysis in the context of health care improvement. In 2018, he published the first systematic review of the ethical issues that are raised for stakeholders in a “learning health care system”. His current research focuses on the ethical oversight of learning health care activities.

Bernhard Zwißler

Bernhard Zwißler is Full Professor and Chair of the Department of Anaesthesiology of the University Hospital of the Ludwig-Maximilians-University of Munich. He served as the elected president of the DGAI (German Society of Anaesthesiology and Intensive Care Medicine) and Editor-in-chief of "Der Anesthesist", the German professional journal for Anesthesiology. As one of few, he is developing a perioperative biomedical informatics training program for anesthetists.

Ulrich Mansmann

Ulrich Mansmann is Full Professor and Chair of the Institute of Medical Information Processing, Biometry and Epidemiology at Ludwig-Maximilians-University of Munich. Ulrich is a trained mathematician who has been working on problems of clinical epidemiology for 25 years. Prognostic models intrigue him and are the central scheme of his scientific activities. He did some methodological research on this topic and applies it to problems in molecular oncology. Ulrich is also interested in building tretament desicion scores. As a biostatistician, he is active in a large series of clinical trials. Since 2005 he holds the chair of biometry and bioinformatics at LMU's Medical Faculty. He is also head of LMU's data integration center. He is member several large national and international medical consortia contributing biostatistical input into their research activities.

Ludwig Christian Hinske

Chris Hinske is a board-certified Anaesthesiologist with cardio- and neurosurgical ICU experience and a Master's degree in Biomedical Informatics from MIT. He is an attending physician and Head of the Perioperative Medical Informatics group at the Department of Anesthesiology of the Ludwig-Maximilians-University Hospital in Munich. His research interests span from bioinformatics models to explore the role of intragenic miRNAs to medical data modeling to improve perioperative patient care. He is coordinating the organization of this conference.

Ben Illigens

Ben Illigens is the CEO of UniMedIT, a subsidiary enterprise of VUD (Verband der Universitätsklinika Deutschlands) and MFT (Medizinischer Fakultätentag) in Germany, with the mission to enhance and innovate Health IT at the German academic hospitals and medical faculties as it relates to patient care, clinical research and medical education and training. He holds an MD degree from Free University of Berlin, Germany, a Master’s Degree in Biomedical Informatics from Harvard Medical School and is a certified Applied Biostatistician. He is a Lecturer of Neurology at Harvard Medical School, the Program Director of the Master’s Program in Clinical Research at Dresden International University, Germany and a continued faculty of the Principles and Practice of Clinical Research course at T.H.Chan School of Public Health, Boston. He is the author of many peer-reviewed papers, several books, recipient of numerous prizes and grants and conducts active collaborations across the world.

Simone Kreth

Simone Kreth is professor of experimental anaesthesiology with a double degree and PhD both in Medicine and Biology. Among her many research interests, she has established a focus in nutritional therapy, especially in cancer patients.

Fady Albashiti

Fady Albashiti is a Medical Informatician holding a PhD from the Ruperto Carola University of Heidelberg, Germany. He is the CEO of the Medical Data Integration Center (MeDICLMU) of the Medical Center of the Ludwig-Maximilians-University (LMU) Munich. Fady has several years industrial experience in agile product, project and innovation management in Telemedicine, Digital Health and Insurance field. Fady worked in different data-based/driven projekts and is convenced, that Data and AI are key, to empower future medicine and will make the difference.

Christopher Sauer

Chris Sauer obtained his Bachelor of Science in Medicine at Maastricht University in 2014, where he was a student representative of the University Council. In the meantime he participated in the Honor’s program in research with a special focus on oncology. For his thesis he was awarded the student price. He deepened his knowledge of oncology at the Dana-Farber Cancer Institute, focusing on Diffuse Large B-cell Lymphoma. He also holds a doctorate from RWTH Aachen University and a Master of Public Health from Harvard T.H. Chan. He currently works as a medical consultant at McKinsey &Company.

Simon Schäfer

Simon Schäfer is a senior attending physician at the Clinic of Anesthesiology, with an expertise in perioperative medicine, intensive care medicine, and healthcare IT. He's active clinically, scientifically, and politically. He has received numerous awards for his research especially in the field of critically ill patients. He serves as a reviewer for multiple high-class medical journals and is associate editor at BMC Anesthesiology. Currently, he is applying methods of Artificial Intelligence to advance coagulation management during complex operations with a high risk of bleeding and emergency care.

Larissa Neumann

Larissa Neumann is a final year resident in Anesthesiology at the University Hospital of the LMU Munich with a two year experience in Critical Care Medicine. Her research focusses on clinical data science and perioperative biomedical informatics. She is fascinated by machine learning and excited about applying methods of Artificial Intelligence in medicine.

Andrea Becker-Pennrich

Andrea Becker-Pennrich holds a Bachelor’s degree in Business Information Systems from the Baden-Wuerttemberg Cooperative State University Mannheim (in cooperation with IBM). Before entering the field of perioperative biomedical informatics she has been working as a paramedic while receiving a Master’s degree in Communications Management. She is currently enrolled at the Ludwig Maximilian University of Munich as a student of Epidemiology and works on her master thesis as a member of the Perioperative Medical Informatics group.

Andre Beinrucker

Andre Beinrucker holds a PhD in Mathematical Statistics from Potsdam University. He has work experience both in industry and academia.

Grigorij Schleifer

Grigorij is a passionate dad and resident in anesthesiology. As clinical investigator at the University Hospital Bonn he is mainly interested in alanlysis of electronic health records in critical care and trauma management. He successfully finished a research fellowship at the Massachusetts General Hospital studying pulmonary circulation and was an instructor for the HST.953 course, collaborative data science in medicine, at MIT. In his spare time, Grigorij learns to program and sings the blues.

Stephanie Lanius

Stephanie graduated from RWTH Aachen (Germany) and Ecole Centrale Paris (France) with a double master's degree in Engineering. Currently, she is working at Philips Acute Care Solutions department where she works on machine learning algorithms for Intensive Care Units. She is fascinated by the chances machine learning offers to advance medicine.

René Eber

René Eber received his M.A. in Business Innovation and is working as a consultant while also pursuing an academic career in computer science. He studied at the University of St. Gallen, Harvard University, the RWTH Aachen and Massachusetts Institute of Technology. His focus is on leveraging machine learning to help companies to gain competitive advantages by bringing together what is strategically desirable and technologically possible.

Niklas Rindtorff

Niklas Rindtorff is a Fulbright fellow at the Broad Institute and an MD/PhD student at Heidelberg University. He received a masters degree in biomedical informatics in 2019 from Harvard Medical School. His research is focused on improving treatment recommendations in precision oncology based on methods such as functional in-vitro testing of patient derived cancer models, clinical image analysis and causal inference of treatment effects. After leading a student-run company during medical school, he remains interested in current developments around digital health. He leads a workshop at this conference.

Louis Agha-Mir-Salim

Louis is a fourth-year medical student at the University of Southampton. Having paused his medical degree for one year, Louis completed a BSc in Medical Sciences with Management at Imperial College London. During his time in London, Louis worked for two digital health start-ups in the field of AI and blockchain. Subsequently, he has acted as participant, mentor, and workshop facilitator at previous MIT Critical Data datathons and workshops in Singapore, Manila, London, and Tokyo. He leads a workshop at this conference.

Our collaboration Partners

Our Sponsoring Partners

Welcome to Munich...

… the most beautiful city in the south of Germany and the capital of Bavaria.

Munich – a city of arts and science - is a place with stunning architecture, an amazing food scene, cordial people, and a rich history. It unifies the Bavarian heritage as well as a vibrant modern lifestyle. Two renowned research universities, multiple global players, research organizations, and a booming start-up scene contribute to its innovative capacity.

...and its sights...

There are bunches of locations you will never forget after visiting Munich. Just to name a few, here is a short list:

Marienplatz (old and new town hall, Frauenkirche, Church of St. Peter), Nymphenburg Palace, English Garden, Munich Residence, BMW Welt, Olympiapark, Alte and Neue Pinakothek, Deutsches Museum, Zoo Hellabrunn, and many more.

Social Event

A major goal of this conference is to bring people excited about using modern technology to advance patient care together.

As we do not want you to leave Munich without a typical Bavarian experience, we would like to invite you to our social event on Wednesday night, which will take place at the beer garden ‚Löwenbräukeller‘. Shaded by chestnut trees, and spoiled with Bavarian food and drinks we would love to spend a memorable time together.

...and its hospitality.

You will fall in love with the beauty of Munich. Especially when the weather is nice and sunny, you can enjoy yourself in the nature in and around the city. Munich is surrounded by spectacular landscapes as the Bavarian lakes and the Bavarian alps.


Data Privacy Statement

Name and Address of the Responsible Person

Responsible in the sense of the EU General Data Protection Regulation (GDPR) and the Data Privacy Regulation of the Federal Republic of Germany (Bundesdatenschutzgesetz) is the
University Hospital of the Ludwig-Maximiliians-University of Munich
Anstalt des öffentlichen Rects (AöR) represented by
Chief Medical Officer
Prof. Dr. med. Karl-Walter Jauch Chief Executive Officer
Markus Zendler
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Name and Address of the Data Privacy Officer

Designated Data Privacy Officer of the University hospital of the Ludwig-Maximilians-University of Munich
Pettenkoferstraße 8
D8o336 München
Phone: +49 (o) 89 44oo 58454
Fax: +49 (o) 89 4400 55192

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D-8o5o2 München
Tel.: o89 212672 o
Fax.: o89 212672 5o

Name and Address of the resopnsible Authority for non-public affairs in Bavaria
Bayerisches Landesamt für Datenschutzaufsicht c/o Regierung von Mittelfranken
Promenade 27
91522 Ansbach
Tel.: o981 53 13oo
Fax: o981 53 9813oo

Change of the Data Privacy Statement

This data privacy statement maybe subject to change secondary to legal or authorative requirements or based on additional features of our website. The most current data privacy statement can be found at .
This website contains links to external websites. We have no influence on and can be held resonsible for the content of these webpages. Importantly, this data privacy statement does not extend to these sites.
If you have questions regarding data privacy, please send an eMail to datathon (at)
Version from March 1st 2019.

Terms and Conditions of Registration

The participation fee for Clinical AI Conference & Datathon Munich 2019 relates to the activities mentioned and outlined on the website. All prices are exclusive of VAT as they are not subject to VAT; this also applies to participants coming from abroad; EU and non-EU.

The participation fee is due after billing. It is only possible to participate if the total amount is paid before May 8, 2019.

The organiser has the right to change the program and venue for organisational or other reasons. Should the conference not take place the conference fees will be returned. Any other claims to the organiser are not valid. Should the conference be delayed the conference registrations remain valid. Product and brand names are usually registered trademarks of the respective companies. The organiser holds all copyrights for the content of the conference.