Invited talks covered new methods and exciting applications of machine learning – including deep neural networks and interpretable AI, cancer and drug toxicity, the social dimension of machine learning, and what machine learning can learn from the way our brains work.
Finally, a keynote lecture by Thomas Lengauer (Max Planck Institute for Informatics & University of Cologne) demonstrated how machine learning predicts drug resistance in HIV and improves the treatment of patients with HIV in very concrete ways.
The event was heavily oversubscribed, testimony of the great interest and strong community in this field. Indeed, (bio)medicine is consistently ranked among the areas where machine learning will have most impact – but it is among the most challenging fields and requires dedicated technology to be applicable and acceptable in the context of biomedical research and clinical practice.
Following the success of this first symposium, a follow-up event is planned for 2020. Please feel free to e-mail Christoph Bock (email@example.com) and Georg Langs (firstname.lastname@example.org) if you have any feedback or suggestions for improvements. Thank you!