Join us for two full days of international and innovative talks by thought leaders and cutting edge researchers in digitalization and infectious diseases.
|07:30 – 08:30||Registration & welcome coffee|
|Chairs: Adrian Egli & Tanja Stadler This first session features an introduction and overview on how digitalization and machine learning will become a key aspects in the future, how does machine learning work, and what are potential use cases in microbiology and infectious diseases?|
|Machine Learning: the new way of personalized medicine Speaker: Julia Vogt, ETH Zurich, Switzerland|
|Machine learning in medicine: Early recognition of sepsis Speaker: Karsten Borgwardt, ETH Zurich, Switzerland|
|Digitalization and machine learning in clinical microbiology Speaker: Jacques Schrenzel, University Hospital Geneva, Switzerland|
|10:30 – 11:00||Coffee break|
Chairs: Belen Rodriguez & Aitana Lebrand
In this session the different approaches for data ontologies and infrastructure will be discussed. What does data need to fulfill, so it can be used for diagnostics and research? What makes data sharable and interoperable? What kind of infrastructure must be in place?
|Next steps for nationwide data networks|
Speaker: Katrin Crameri, Data Coordination Centre and SIB Swiss Institute for Bioinformatics, Switzerland
|Ontologies fit for machine learning|
Speaker: Claire Bertelli, University Hospital Center of Lausanne, Switzerland
|12:00 – 13:45||Lunch & poster session|
Chairs: Richard Neher & Jacob Moran-Gilad
In this session “studies” will be the focus. Are there particular aspects one need to consider during study design? What is the potential of digitalization and machine learning in single and multi-center studies. How can studies be compared?
|What is a good control group? How to use public data?|
Speaker: Ernst Hafen, ETH Zurich and MiDATA, Switzerland
|Machine learning in sepsis: Lessons learned for digitalization and infectious disease|
Speaker: Christopher W. Seymour, University of Pittsburgh, United States of America
|Sharing is caring: Moving toward a global database for critical care|
Speaker: Ryan Kindle, Massachusetts Institute of Technology and Harvard/Massachusetts General Hospital/Beth Israel Deaconess Medical Center Combined Program, United States of America
|15:15 – 15:45||Coffee break|
Chairs: Jürg Blaser & Aitana Lebrand
Within this session concrete clinical applications and use cases of machine learning algorithms should be discussed in more detail – the key aspects of diagnostics, therapy and epidemiology will be addressed.
|Artificial intelligence to improve empiric antibiotic treatment|
Speaker: Carolina Garcia-Vidal, Hospital Clinic of Barcelona, Spain
|Personalized and public health with machine learning|
Speaker: Marcel Salathé, École Polytechnique Fédérale de Lausanne, Switzerland
Chairs: Gilbert Greub & Sarah Tschudin Sutter
The last session of the day zooms out for a broader perspective and overview on opportunities, challenges, and risks of digitalization and machine learning in clinical applications. Can patients with infectious diseases be recognized based on machine learning? What are sensitivities and specificities?
|Opportunities of digitalization and machine learning in clinics |
Speaker: Adrian Egli, University Hospital Basel, Switzerland
|Challenges and risks of digitalization and machine learning in clinics |
Speaker: J. Janne Vehreschild, University Hospital Cologne, Germany
Expert discussion panel: Usage of machine learning in clinics
Speakers from the day address most urgent questions and discuss solutions
Panel (moderator Paul Savelkoul) Claire Bertelli, Karsten Borgwardt, Adrian Egli, Ernst Hafen, Ryan Kindle, Marcel Salathé, Jacques Schrenzel, Christopher W. Seymour, J. Janne Vehreschild, Julia Vogt
|18:30 – 19:15||Swiss winter networking apéro|
|08:00 – 08:30||Registration & welcome|
Chairs: Nicole Ritz & Urs Frey
In this session the specific aspects of digital tools, machine learning and use of big data for pediatric infectious diseases are the focus. Developments of tools particularly useful in low resource settings, challenges in the development of digital tools in pediatrics, and use of digital tools to improve vaccine coverage worldwide will be discussed.
|Digital tools for diagnosis of infections in low-income settings|
Speaker: Kristina Keitel, Swiss Tropical and Public Health Institute and University Hospital Bern, Switzerland
|Challenges in developing, validating and implementing clinical decision support algorithms|
Speaker: Valérie D’Acremont, Swiss Tropical and Public Health Institute and University of Lausanne, Switzerland
|Deep learning reveals patterns of specificity in adaptive immunity|
Speaker: Sai Reddy, ETH Zurich and Botnar Research Centre for Child Health, Switzerland
|10:00 – 10:30||Coffee break|
Chairs: Paul Savelkoul & Jürg Blaser
Ethical, quality and legal regulations and requirements regarding machine learning in the context of infectious diseases and microbiology will be highlighted and discussed. Are there particular ethical, quality or legal aspects researchers should consider using digital and machine learning technologies? The talks will use (if possible) clinical cases with diagnostic and treatment related aspects of infectious diseases as basis and from there, discuss ethical, quality and legal issues.
|Ethical and legal challenges of artificial intelligence and big data |
Speaker: Susanne Driessen, SwissEthics, Switzerland
|Social impact and risk governance of machine learning in the context of infectious diseases|
Speaker: Marie-Valentine Florin, École Polytechnique Fédérale de Lausanne, Switzerland
|Medical Devices: Regulatory requirements — a jump start|
Speaker: Christian Johner, Johner Institut, Germany
|Data security in digitalization and machine learning|
Speaker: Jean-Pierre Hubaux, École Polytechnique Fédérale de Lausanne, Switzerland
|12:30 – 14:15||Lunch & poster session|
Chairs: Sarah Tschudin Sutter & Belen Rodriguez
This session will focus on the “next steps” for implementation taking the view of different stakeholders – the focus will be on needs and actions from clinics and early career academia and start ups in order to implement digitalization and machine learning to improve the diagnostics and treatment of infectious diseases.
|Incorporating AI into clinical practice: Opportunities and challenges|
Speaker: Ken P Smith, Beth Israel Deaconess Medical Center and Harvard Medical School, United States of America
White-box machine learning insights into antibiotic efficacy
What do we need from start-ups and early career (Flash talks from selected abstracts)
Machine learning to parameterise individual-based models of malaria transmission
Tuberculini: Combining targeted sequencing and machine learning to optimize antibiotic therapy in tuberculosis patientsSpeaker: Sebastian Dümcke , start-up Clemedi AG and University of Zürich
Rapid, Reproducible Resistance Analysis for All – The AMR Package for R Speaker: Matthijs Berends, University of Groningen, Netherlands and Certe Medical Diagnostics and Advice, Netherlands
|16:15 – 16:45||Coffee Break|
Chairs: Karsten Borgwardt & Gilbert Greub
This session continues the focus on the “next steps” for implementation taking the view of different stakeholders – the focus will be on needs and actions from non-profits and academia in order to implement digitalization and machine learning to improve the diagnostics and treatment of infectious diseases.
|Implementation of digital solutions in low, middle income countries |
Speaker: Rigveda Kadam, Foundation for Innovative New Diagnostics, Switzerland
How does digitalization affect the management of infectious diseases?
|17:45 – 18:15||Conclusions and conference closing|