AI in Cancer Care Symposium
How Will AI Transform Cancer Care by 2030?

Thursday 30 April 2026
14:30PM - 18:35PM

Langhans Hörsaal
Inselspital, Bern

Artificial Intelligence (AI) is rapidly transforming both our daily lives and professional practices and is expected to profoundly reshape how cancer care is delivered in the coming years. Join us for a focused half-day symposium exploring how AI is expected to transform cancer care over the next decade.

Bringing together international, national, and local experts, the program will provide a comprehensive, practice-oriented perspective on how AI is being integrated across the oncology pathway, from diagnosis to treatment, including the patient perspective.

Designed for clinicians, researchers, and healthcare professionals, the symposium offers actionable insights into real-world applications, emerging developments, and the opportunities and challenges shaping the future of AI in oncology. Secure your place and be part of the conversation.

Meet Our Speakers

Daniel is a Professor of Medicine at University Hospital Aachen, where he leads the Laboratory for Artificial Intelligence in Medicine. His work focuses on translating AI methods into clinical routine, with a particular emphasis on accelerating the deployment of AI models in oncology. With a background in both physics and medicine, his research bridges methodological innovation and real-world clinical application. In his talk, he will discuss agentic AI systems and their potential to transform diagnostic and therapeutic decision-making in clinical medicine.

Prof. Dr. Alexander Pöllinger is a board-certified radiologist and Clinical Head of Thoracic Radiology at the University Institute of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, Switzerland. He previously held senior leadership roles at Charité - Universitätsmedizin Berlin and completed his medical training at Goethe University Frankfurt, with research appointments at Harvard Medical School (MGH). His academic work focuses on thoracic imaging, quantitative lung diagnostics, and artificial intelligence in radiology. Prof. Pöllinger has authored more than 90 peer-reviewed publications and has served as principal investigator and co-investigator on multiple nationally funded research projects, including Swiss National Science Foundation grants

After completing his double degree in human medicine and Medical Life Sciences at the Technical University of Munich, Bastian Dislich completed his pathology training at the Institute of Pathology at the University of Bern. There he works as a senior physician in the departments of gastrointestinal pathology, soft tissue pathology, hematopathology and molecular pathology. His research focus is on carcinomas of the gastroesophageal junction and the stomach.

Prof. Sarah Brüningk is leading the Center for AI in Radiation Oncology at the University Hospital Bern and the University of Bern, Switzerland. She is a physicist by training (TU Munich, Germany) and completed a PhD at the intersection of practical wet lab and computational biology at the Institute of Cancer Research (UK) before moving to ETH Zurich as a postdoctoral researcher focusing on AI for biomedical applications. Her research harnesses combinations of mathematical modelling and advanced machine learning to process multimodal data spanning from omics to imaging for applications in oncology and pediatric digital health.

Prof. Guido Beldi is the chief physician of Visceral Surgery and Medicine at Inselspital Bern. He is a leading surgeon whose research interests include AI-assisted surgical decision support, peri-operative risk modelling and the use of real-world data to improve outcomes in abdominal oncology.

Prof. Kuangyu Shi is the Chief Medical Physicist and Head of the Lab for Artificial Intelligence and Translational Theranostics at the Department of Nuclear Medicine, University of Bern. He is also a senior lecturer at TU Munich. His research advances AI and computational modeling for nuclear medicine imaging, dosimetry and therapy, linking outcomes with underlying pathophysiology, and developing in vivo and ex vivo experimental methods for microscopic nuclear imaging. He is involved with EANM AI initiatives and ICRP task groups and serves on editorial boards in the field.

Prof. Andreas Wicki is a senior oncologist and haematologist at University Hospital Zurich, with a focus on targeted therapies and AI-driven approaches to treatment stratification. His translational research investigates biomarkers and computational tools to guide personalised cancer therapy.

Chantal Britt holds an MA in Translation from the University of Geneva. She worked 13 years as a financial and science journalist at Bloomberg News and Swissinfo.ch, then a decade in science communication and public affairs for non-profits across health and research. After developing long Covid in 2020, she co-founded Long Covid Switzerland and chairs Long COVID Europe. She contributes to patient involvement, citizen science, and participatory research, and serves on several patient advisory and network boards in Switzerland.

Stavroula G. Mougiakakou is an Associate Professor and holds a Ph.D. degree in computer engineering from the National Technical University of Athens. Since 2008 she is affiliated with the Faculty of Medicine, University of Bern and Head of the AI in Health and Nutrition Laboratory (former Diabetes Technology Research Group) at the ARTORG Center for Biomedical Engineering Research Bern, Switzerland. Her current research interests include artificial intelligence, machine learning, computer vision and advanced data analysis to improve health by providing solutions for better diagnosis, personalized treatment and dietary assessment.

Professor Mauricio Reyes began his academic journey in 2003 when he was awarded a French-Chilean scholarship to conduct his PhD studies at INRIA, France. His research focused on AI technologies to improve cancer workflows and led to novel image reconstruction techniques for respiratory motion compensation in PET imaging. Through EU-funded projects, he developed AI solutions for neuro-oncology, with a focus on automated brain tumor assessment. He received the MICCAI Young Scientist Publication award in 2016 and has pioneered robust and explainable AI in medical image analysis.

Dr. Michael Stickel is Chief Medical Information Officer (CMIO) at the Insel Gruppe in Bern, where he leads the strategic integration of clinical practice and digital health systems. With a background in surgery and emergency medicine, he brings extensive frontline clinical experience to the development and implementation of hospital information systems. He has been closely involved in large-scale electronic health record implementations, including EPIC-based systems, and holds advanced certifications in health informatics, clinical documentation, and SNOMED CT. His work focuses on aligning digital innovation with clinical work.

Program

14:30 | Welcome

14:35 | Keynote: "Agentic AI"

15:05 | Together on our Patient's Journey: AI-Enhanced Diagnostics

15:50 | Coffee Break & Networking

16:20 | Together on our Patient's Journey: AI in Cancer Therapy

17:05 | Coffee Break & Networking

17:35 | Reality Check

18:35 | Apéro & Networking

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Department of Digital Medicine (DDM)