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Keynotes and Workshops

Introduction (E)

Prof. Dr. Sven Hirsch, Leiter ZHAW Digital Health Lab

The Swiss healthcare system faces a huge opportunity. In this past pandemic year we have witnessed the necessity for efficient data flows and concerted organizational processes. We have seen that trust, in the form of data security, privacy and institutional integrity is a prerequisite for functioning care of both individual and public health. Now that the systemic deficiencies became apparent to everyone, we need to take on the challenge of creating the next level smart health care system. The concept «liquid hospital» describes a people-centric care approach with integrated delivery of services outside and in the hospital. This vision requires trusted digital infrastructure to connect patient and care personal, and it asks for new ways of interaction. We have to show the potential benefits to the people in controlled settings. We need to deliver digital health solutions that offer care that is accessible, excellent, and affordable.

Sven Hirsch is a trained interdisciplinary physicist in the field of biomedical simulation and digital art. His mission is to develop data-driven disease models to drive clinical decision making. His research team at ZHAW uses machine learning to tackle signal analysis and computer vision tasks and applies statistical methods. They embrace applied research questions and collaborate with industry. He has contributed to radiomic characterization of intracranial aneurysms, thrombosis modelling, tumor & angiogenesis growth modeling, and modelling of biotech and food processes. He invented a novel digital holography system for facial topography at the Univ. Düsseldorf in collaboration with the University Hospital Basel. Then, he joined the computer vision group of Prof Székely at ETH Zürich to establish a biomedical simulation team. Before, Sven Hirsch worked as a media artist, holding a postgrad degree in audiovisual media from KHM Cologne and a physics diploma from Univ. Heidelberg. He directs the ZHAW digital health lab to innovate patient-centered data-driven health care in Switzerland and beyond.

Keynote «AI Solutions in Clinical Care» (E)

Prof. Dr. med. Michael Krauthammer, Medizinische Fakultät, Universitätsspital Zürich, Medizininformatik

This talk will discuss applications of AI in the healthcare setting. The talk will review the range of autonomous, assistive and background AI solutions that are currently being deployed in clinical practice. In addition, the talk will highlight ongoing clinical AI research at the University of Zurich and University Hospital of Zurich. 

Michael Krauthammer is Professor and Chair of Medical Informatics at the University of Zurich and Managing director of Biomedical Informatics at the University Hospital of Zurich. He graduated from medical school at the University of Zurich to later complete a Ph.D. in Biomedical Informatics at Columbia University in New York, USA. After completion, he joined the Department of Pathology and Center for Medical Informatics at the Yale University School of Medicine where he led a research group in translational informatics. In 2018 he moved back to Switzerland to continue his work at the University of Zurich. Current research in bioinformatics includes cancer genomics using novel technologies (long-read and single-cell sequencing) in order to improve cancer diagnostics and monitoring. In clinical data science, topics include prediction of drug-drug interaction, natural language processing in electronic medical records, and the use of machine learning & AI in clinical decision making.

Keynote «Key Insights from the Digital Health Report 2021» (E)

Prof. Dr. Alfred Angerer, Leiter Management im Gesundheitswesen, Winterthurer Institut für Gesundheitsökonomie

Every second year, Mr. Angerer and his team publish a report for practitioners on the state of digital health in the Swiss healthcare system. In his presentation, Mr. Angerer will depict the core messages of the 2021/22 report to the public for the very first time. The presentation will first focus on the digital health market in Switzerland and worldwide from a business point of view. Furthermore, selected major events and best practices from the year 2020/21 will be presented and their impact on the digitalization of the healthcare system analyzed. The results of the survey of health experts on Digital Health trends and forecasts round off the presentation.

Prof. Dr. oec. Alfred Angerer studied industrial engineering and business science at the University of Karlsruhe and completed a doctorate in business administration at the University of St. Gallen. He has gained practical experience as a supply chain manager at Nestlé AG and as a management consultant in operations at McKinsey & Company. Since 2009 he has been a lecturer at the ZHAW School of Management and Law. There he heads the Center for Health Care Management of the Winterthur Institute of Health Economics and is co-director of the Digital Health Lab. Mr. Angerer is a member of the advisory board of several digital health startups and a member of the Canton Thurgau Health Commission. His research focuses on digital health and process optimization (lean healthcare). Mr. Angerer is the creator of numerous international publications, books, lectures and the podcast "Marketplace Healthcare" that deals with the management of healthcare organizations in the digital age.

a) Smart Medical & Healthcare Logistics (D/E)

Prof. Dr. Thomas Ott (ZHAW), Dr. Lukas Hollenstein (ZHAW), Peter Kauf (Prognosix AG)

Logistik- und Planungsprozesse bilden das Rückgrat für ein funktionierendes Gesundheitssystem. Gerade die Covid-19-Krise hat die grosse Bedeutung dieser Prozesse sichtbar gemacht. Digitale Werkzeuge, wie Simulationen oder Optimierungen mittels künstlicher Intelligenz, können dabei entscheidende Beiträge leisten, die Prozesse effizient und effektiv zu gestalten.

In unserem Workshop wollen wir uns zunächst einige besonders erfolgreiche Use Cases anschauen und dann in einer gemeinsamen Diskussion den Blick schärfen für bestehende Herausforderungen und Lösungsansätze.

b) Der Einsatz von Virtual Reality und Video in der Therapie – ein Experiment (D)

Maria Auer (ZHAW), Dietlinde Arbenz (ZHAW)

Wir nehmen Sie auf einen virtuellen (VR) Klientenbesuch mit. Dabei tauchen Sie in die Lebenswelt von Yvonne Luginbühl ein und erleben ihre Herausforderungen und Bewältigungsstrategien im Alltag. Wie könnten andere betroffene Menschen von den Strategien und Erfahrungen profitieren und welche Rolle könnte dabei das Medium Video spielen?

c) Datenökosystem für Gesundheit und Forschung: eine Multi-Stakeholder-Herausforderung für eine moderne und wettbewerbsfähige Schweiz (D/E)

Prof. Serge Bignens (BFH), Dr. Philipp Ackermann (ZHAW)

Die Digitalisierung im schweizerischen Gesundheitswesen ist verbesserungswürdig wie aktuelle Vorkommnisse beim BAG, bei meineimpfungen.ch, beim digitalen Patientendossier zeigten und insbesondere beim fehlenden offenen Gesundheitsdaten-Ökosystem. Was sind die Gründe und welche Rolle sollen Fachhochschulen zukünftig einnehmen?

d) Beyond clinical trials – how to get an insight into the dynamics of disease development and therapy response (D/E)

Prof. Dr. Stephan Scheidegger (ZHAW)

As a pillar of evidence-based medicine, clinical trials and meta-analysis of trials generate knowledge regarding the effectiveness of therapies (therapy A better than therapy B etc.). A more profound understanding of the dynamic aspects regarding disease development or treatment response beyond this knowledge would require novel research methodologies. As a complementary approach to biological experiments in vitro, in vivo or clinical trials, computer simulations may help to understand the dynamics in complex biological systems on the scale of cells, patients or populations. The aim of the mathematical models used for this purpose (model-based data analysis) is to identify dynamic patterns which can be compared with real-word data for detecting similar dynamic processes responsible for disease progress or therapy outcome.

To showcase this concept of model-based analysis in medicine, different examples (semantic modelling in immunology and oncology; systems epidemiology) are presented. After an input talk, the following points are aimed to be discussed:

e) Agiles Management von Personalkapazitäten im Gesundheitswesen (D)

PD Dr. Florian Liberatore (ZHAW) Dr. Alain Meyer (Careanesth), Sarah Schmelzer (ZHAW)

Die Potentiale digitaler Plattformen zur schnellen und flexiblen Vermittlung von Personalressourcen im Gesundheitswesen haben sich besonders in der Corona-Pandemie gezeigt und ihre Verbreitung und Funktionalität wird einer dynamischen Entwicklung unterliegen. Die Firma Careanesth ist führend bei der Vermittlung von temporär arbeitenden Pflegefachpersonen über digitale Plattformen.

Ausgehend von einem Einblick in die gegenwärtige Funktionsweise der Careanesth Plattform werden mit den Teilnehmenden folgende Inhalte erarbeitet und kritisch diskutiert:

  1. weitergehende Einsatzfelder im Gesundheitswesen
  2. Weiterentwicklung der Plattform-Funktionalitäten 
  3. digitaler Arbeitsvermittlungsplattformen und Kapazitätsmanagement

f) AI (Artificial Intelligence) Powered Medical Image Analysis – from Imaging to Decision Support (E)

Dr. Norman Juchler (ZHAW), Mohammadreza Amirian (ZHAW), Dr. Javier Montoya (ZHAW)

Medical imaging constitutes a key source of information to address clinical and scientific questions. In order to improve image acquisition, to better handle the wealth of data contained in images, or to help clinicians make better decisions, methods that fall into the realm of artificial intelligence (AI) are increasingly being used.

This workshop provides an overview of the manifold applications of AI in conjunction with medical imaging. We broadly categorize the methods into information acquisition, information processing and information application. Based on this, we present a selection of approaches that illustrate the potential of AI-based methods, their impact in clinical practice, and remaining challenges.

Clearly, the field of AI-driven medical imaging is far too large to cover all relevant aspects in a single workshop. Instead, we take an application-oriented approach that also includes the practical experience of our collaborators in industry and clinics.

g) Die Nutzenden haben immer recht: Qualitative und quantitative Erhebung ihrer Anforderungen an Rehabilitationstechnologie (D)

Dr. Eveline Graf (ZHAW), Mandy Scheermesser (ZHAW), Leah Reicherzer (ZHAW)

Der Workshop vermittelt verschiedene Methoden zur Erhebung der Anforderungen der Nutzenden. Erleben Sie die Perspektive der Nutzenden anhand konkreter Beispiele und erfahren Sie Rehabilitationstechnologie.

a) Anti-Black Box – Causal Modelling for Clinical Data (E)

Dr. Georg Spinner (ZHAW), Matteo Delucchi (ZHAW)

Machine learning promises to revolutionize medicine and will increasingly change clinical work. Many tasks can be performed by machines with often astonishing accuracy. However, this increasing automation also forces the methods to be transparent and traceable by people. For this purpose, interpretable methods will be discussed at this workshop. Probabilistic graphic models allow the statistically rigorous modeling of complex relationships in large data sets, whereby the resulting model can also be communicated to laypeople. This qualitative and quantitative integration of knowledge and data should help to make a comprehensible, data-driven clinical decision and also reveal causal relationships between various diseases.

b) Präventive Gesundheitsversorgung der Zukunft (D)

Dr. Samuel Wehrli (ZHAW), Andri Färber (ZHAW), Prof. Dr. med. Barbara Biedermann (COBEDIAS Institut)

Wie schaut die Gesundheitsversorgung in Zukunft aus? Nach welchen Kriterien und wann werden in Zukunft Menschen hospitalisiert? Digitale Lösungen (z. Bsp. Wearables, mobile Apps, intelligente Lautsprecher) haben das Potential, sich anbahnende, gesundheitliche Krisen früher zu erkennen und weniger invasiv zu behandeln.

In diesem interaktiven Workshop gehen wir zwei Szenarien auf den Grund. Nach einem kurzen Input-Referat erarbeiten die Workshop-Teilnehmer Antworten auf die folgenden Fragen:

c) Roboter im Gesundheitsbereich – vor welchen Möglichkeiten und Herausforderungen stehen wir? (D)

Prof. Dr. Maria Schubert (ZHAW), Nicole Zigan (ZHAW), Iris Kramer (ZHAW)

Roboter – insbesondere Assistenzroboter und soziale Roboter – halten zunehmend Einzug in den Gesundheitsbereich. Sie sollen die Patientinnen und Patienten und das Gesundheitspersonal im Alltag sowie in der Pflege und Betreuung unterstützen. Einige bewegen sich selbstgesteuert und mit ihren sozial-kommunikativen Funktionen können sie mit Menschen interagieren und sogar bei ihren Gegenüber Gefühle auslösen. Welche Einsatzpotenziale ergeben sich mit den neuen Playern im Gesundheitswesen und welche Risiken sind damit verbunden?

Dieser Workshop gibt zunächst einen Überblick zum aktuellen Entwicklungsstand dieser Roboter und deren gegenwärtigen Einsatz im Gesundheitswesen mit hierzu verfügbaren Forschungsergebnissen. Danach diskutieren die Teilnehmenden in Gruppen die Einsatzmöglichkeiten, Arbeiten und Aufgaben, die diese Roboter im Schweizer Gesundheitsbereich übernehmen sollen, sowie welche Chancen und Risiken hiermit verbunden sind.

d) Serious Games in der Gesundheitsförderung – Spielerisch Schreibmotorik fördern (D)

Dr. Annina Zysset (ZHAW), Prof. Dr. Frank Wieber (ZHAW), Prof. Dr. Ulrich Götz (ZHdK Game Design)

Zu Beginn geben zwei Inputs zum Gaming Approach und digitalen Interventionen zu Änderungen des Gesundheitsverhaltens einen Überblick über die beiden Ansätze und ihren Berührungspunkten.

Anschliessend konkretisieren wir anhand des laufenden Projektes «Schreibmotorik von Schulkindern spielerisch fördern mit Hilfe eines Serious-Games», wie die Schritte von der Idee zum Spiel-Konzept ablaufen, wie das interdisziplinäre Team im Projekt zusammenarbeitet und wie die Implementierung geplant ist.

Ausgehend vom Anwendungsbeispiel werden gemeinsam Themen gesammelt und ausgewählt, die dann in Kleingruppen weiter diskutiert werden. Ziel ist es, dass die Teilnehmenden das Thema Serious Games aus ihrer fachlichen Perspektive betrachten und so Chancen und Herausforderungen explorieren können. 

Abschliessend stellen wir die Ergebnisse der Kleingruppen im Plenum kurz vor und diskutieren gemeinsam konkrete Anschlussmöglichkeiten und generelle Implikationen.

e) Biodesign – The Silicon Valley Method for disruptive Digital Health Innovation (E)

Dr. Jens Haarmann (ZHAW)

The workshop provides an overview into Stanford’s Biodesign innovation process to identify major market opportunities and invent high potential digital health solutions. It is for scientists, physicians and business professionals interested to lead complex, interdisciplinary digital health projects within their organisation, or create high growth startups.

f) Trust in Medical AI (Artificial Intelligence) Systems (E)

Prof. Dr. Ulrich Reimer (Ostschweizer Fachhochschule), Dr. Holger Rommel (ti&m), Dr. Beat Tödtli (Ostschweizer Fachhochschule), Prof. Dr. Katarzyna Wac (Universität Genf)

Artificial Intelligence (AI) systems are beginning to have an impact in the medical domain. This raises the question what will make physicians (and thus patients) trust such a system. Trust is influenced by many factors, primarily

Since medical AI systems are considered medical devices, they need to be certified by an officially recognized agency or regulatory body. By assuming responsibility for the adequacy of the medical AI system, regulatory bodies provide an established source of trust, freeing physicians from establishing trust themselves. However, certification of a complex software system does not guarantee that it is free of errors.

After an introductory presentation, we will discuss various trust-inducing factors (technical and non-technical ones) in smaller, parallel groups. The results from the groups will then be presented and discussed in the whole group of participants.

g) Designing inclusion into digital health from the start (E)

Piera Marongiu (HBA Zurich Zug), Sean Yap (HBA Zurich - Zug)

Currently, there are major blind-spots in the digital technologies that support early detection, diagnosis, treatment and follow up, the AI systems behind. The conventional development process is tested on narrow cohorts but applied to wide and diverse population.

Ignoring social inclusion in product development can be more than just financially costly to all parties. It limits the efficacy of the AI algorithms and the accurate detection of symptoms by physicians, affects the treatment and limits the usefulness of medical devices.

Personalized and precision medicine in the form of inclusion, as opposed to the conventional “one size fits all” model, is the future of healthcare. A future that recognizes and treats people based on their specific characteristics be it ethnicity, gender or preferences.

Brought to you by the Zurich – Zug chapter of Healthcare Businesswomen’s Association (HBA), this will be an essential session with workshops to help apply this thinking in pre-creation phase, as well as along the development process.

Keynote «Multimodal Machine Learning for Quality of Life Assessment: Throwing Data at a Problem?» (E)

Prof. Dr. Katarzyna Wac, Full Professor of Computer Science, Quality of Life Technologies & mQoL Living Lab Director, Center of Informatics, University of Geneva

Patterns of diseases are changing. They relate less and less to sudden infections or crippling accidents. On a growing scale, they develop as slow and debilitating afflictions caused by repetitive harmful behaviours (e.g., lack of sleep, poor nutrition). These behaviours relate to different domains - the physical, psychological, social, and environmental - and contribute significantly to the individual’s overall health and Quality of Life (QoL) in the long term. In parallel, the ubiquitous availability of personalized technologies embedded in smartphones and wearables enable longitudinal, real-life, objective, minimally obtrusive, multimodal modelling of the individual’s behaviours, health risks, and the resulting QoL in the long term. This talk motivates the need for and presents the rise of these multimodal modeling methods while following the 24 sub-domains of the World Health Organization Quality of Life model (WHOQOL). The research on multimodal modeling fills a gap in the field of QoL assessment methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor, and focusing mainly on the compensatory role of personal technologies. Therefore, the talk presents the state-of-the-art in the field and critically appraises the multimodal modeling efforts. Also, it highlights the human-centric success factors for the adoption and scaling of technology-enabled methods and tools for QoL assessment leveraged for behavior change, health management, disease prevention, and QoL enhancement in the long term in populations at large.

Katarzyna Wac, PhD, is a Full Professor of Computer Science at the University of Geneva, Switzerland and an Invited Professor of Health Informatics at the Department of Computer Science (DIKU), University of Copenhagen, Denmark. Prof Wac leads Quality of Life (QoL) Technologies lab which research interests revolve around the fundamental and algorithmic problems of systems enabling an assessment and improvement of human behavior, health and quality of life in the long term. Prof Wac is a (co)-PI in several European (including H2020), Swiss NSF projects and Stanford Medicine projects. Prof Wac contributes to the ITU’s European Regional Initiative for mHealth and well as consults industry on the topics related to Digital Health. Prof Wac is a keynote speaker, a teacher, and a mentor, and in 2015 was a TEDMED Research Scholar. Prof Wac is also a Senior Member of ACM and the IEEE.