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Keynote Lectures

Wirewalking over two medical AI chasms. Results and open problems in making "valid AI" also useful in medical practice.
Federico Cabitza, Università degli Studi di Milano-Bicocca, Italy

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Christoph Hölscher, ETH Zurich, Switzerland

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Katja Bühler, VRVis, Austria

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Claudia Pagliari, University of Edinburgh, United Kingdom

 

Wirewalking over two medical AI chasms. Results and open problems in making "valid AI" also useful in medical practice.

Federico Cabitza
Università degli Studi di Milano-Bicocca
Italy
 

Brief Bio
Federico Cabitza, MEng, PhD, is an Associate Professor at the University of Milano-Bicocca (Milan, Italy) where he teaches Human-Computer Interaction and where he coordinates the research activities of the MUDI Lab (Modelling Uncertainty, Decisions and Interaction). Since 2016 he has also had a research appointment with the IRCCS Orthopaedics Institute Galeazzi in Milano (Italy) and more recently with San Raffaele Hospital. He is associate editor of the International Journal of Medical Informatics (IJMEDI, ISSN: 1386-5056) and stable member of the editorial boards of the MAKE - Machine Learning and Knowledge Extraction journal (ISSN: 2504-4990), the CRCL Cross-Disciplinary Research in Computational Law (ISSN 2736-4321), and the Journal of Medical Artificial Intelligence (ISSN 2617-2496). He has co-chaired International workshops (on Data Visualization in Healthcare and knowledge IT artifacts), conference tracks (on Socio-technical design), conference programs (for the Italian Chapter of AIS and BIOSTEC Healthinf in 2020) and special issues on impacted Journals (i.e., the CSCW journal, Program, and the Health Informatics Journal). He is the author of more than 140 research publications to date, in international conference proceedings, edited books and scientific journals, including the JAMA, the CSCW Journal, Computers in Biology and Medicine, Behaviour and Information Technology, International Journal of Human Computer Studies, Computers in Human Behavior, International Journal of Approximate Reasoning, and the Journal of Visual Languages and Computing. His current research interests regard the design and evaluation of interactive systems and decision support based on machine learning techniques in the Healthcare domain.


Abstract
Achieving a pragmatic, or even an ecological validation (Cabitza and Zeitoun, 2019) of medical AI systems that nevertheless exhibit very high (statistical) accuracy has been observed to be more complicated than initially expected (Coiera et al. 2018): in fact, most of the challenges that make technically sound systems perform poorly in real-world settings lie in the so called “last mile of implementation” (Coiera, 2019). This evocative concept expresses the semantic difference between developing medical machine learning (or medical AI) and the mere application of machine learning techniques to medical data. Moreover, we will make the point that the space bewtween machine learning development and clinical practice, is not a flat and regular path, but rather presents two chasms: the chasm of human trust, and the chasm of machine experience. The former one requires to focus on usability and explainability, while the latter ones requires data governance and to focus on data work, including practice of “data awareness” and “data hygiene”. I will discuss these notions, and report about some researches I personally conducted while trying to bridge the above chasms with mixed fortunes: what we recognize as still open problems are exciting opportunities to look at a seemingly established field from a fresh perspective (the interactionist perspective) and develop solutions that focus on the utility of the technology rather than following the mirage of accuracy.



 

 

Keynote Lecture

Christoph Hölscher
ETH Zurich
Switzerland
 

Brief Bio
Christoph Hölscher is Full Professor of Cognitive Science in the D-GESS at ETH Zürich since 2013, with an emphasis on Applied Cognitive Science. Since 2016 Christoph is a Principal Investigator at the Singapore ETH Center (SEC) Future Cities Laboratory, heading a research group on ‘Cognition, Perception and Behaviour in Urban Environments’. Christoph is the Program Director of Future Resilient Systems FRS at the SEC since 2019, leading the current FRS 2 phase (2020-2025). He holds a PhD in Psychology from University of Freiburg, served as honorary senior research fellow at UCL, Bartlett School of Architecture, and as a visiting Professor at Northumbria University Newcastle. Christoph has several years of industry experience in Human-Computer Interaction and usability consulting. The core mission of his research groups in Zurich and Singapore is to unravel the complex interaction of humans and their physical, technical and social environment with an emphasis on cognitive processes and task-oriented behavior.


Abstract
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Keynote Lecture

Katja Bühler
VRVis
Austria
 

Brief Bio
Katja Bühler is Scientific Director of the VRVis Research Center in Vienna, Austria. She completed her studies in Mathematics at KIT, Karlsruhe, Germany and holds a PhD in Computer Science from TU Wien, Austria. In 2003 she became head of the Biomedical Image Informatics Group at VRVis. She is member of the management board of Austrian Bioimaging and associate editor of Computers and Graphics, the Visual Computer and Frontiers in Bioinformatics. Katja’s scientific roots are in reliable computing, numerics and geometry processing. Today's focus of her research is on the development of highly efficient methods to provide access to information encoded in biomedical images with the aim to accelerate image-based decision making. For this purpose, she is fusing expertise in image processing, machine and deep learning, high performance computing, data mining, visualization and human computer interaction to novel visual computing solutions for medicine and life science. Research results of her group received numerous scientific awards and resulted in several patents. The software emerged from the groups research is helping radiologists, radiotherapists and surgeons to cope with multi-modal images and diagnostic tasks in their daily clinical routine. The e-science platform Brain* addresses the urgent need to manage and exploit image intense data collections and accelerates multi-omics and image-based research of neuroscientists.


Abstract
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Keynote Lecture

Claudia Pagliari
University of Edinburgh
United Kingdom
 

Brief Bio
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Abstract
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