HISS2024 – Health Innovation Summer School

The information will be updated continuously.

Artificial Intelligence, innovation and implementation – enhancing healthcare ecosystems through information driven care

Healthcare systems are complex and multifaceted. Digital technologies hold great potential for enhancing healthcare, empowering healthcare professionals, improving access and equity, and delivering better health outcomes.

This summer school aims to support doctoral students understand artificial intelligence’s (AI) potential to improve healthcare ecosystems. Topics covered will enable students to think strategically with multidisciplinary knowledge on information driven care, connecting the fields of AI and machine learning (ML), innovation and implementation.

At HISS, doctoral students will have the opportunity to discuss in lectures and creative workshops together with distinguished key note speakers and in-house researchers.

The summer school is part of the University's focus area Health Innovation and the research programme Information driven care (IDC).

Cross-disciplinary exchanges

Participating students come from multinational and cross-disciplinary backgrounds, creating a melting pot of competence and inspiration. This course offers a unique opportunity for you to be a part of creative and innovative processes. During the last day of the course you will present your interdisciplinary project work and listen to fellow students‘ perspectives as a final pitch.

HISS is a perfect way to extend your personal network and create international contacts. It might be the start of a fruitful relationship.

Is this for you?

We encourage doctoral students with a background in any of the following academic fields of AI/ML, innovation, health, medical and implementation sciences, and who are curious about the integration of these perspectives for the objective of enhancing information driven care to apply for this summer school at Halmstad University.

Come join other doctoral students in Halmstad next August for summer, sun and science!

Practical information

• When fulfilling all required activities, the course represents 5 credits.
• The fee is 2,500 SEK per student (from Swedish authorities). SEK 3,125 (including VAT 625 SEK) for all other payments.
• The registration of the summer school is available via the registration form at this webpage.
• The last day of registration is on May 27, 2024.
• Number of participating students are limited to 25.
• The price includes tuition, welcome reception, lunches and “fika” during the course.

Register for the Summer School

Last day for registration is May 27, 2024. If you are accepted to the course, you will receive an email with further information and payment details.

Meet our key note speakers

Thomas Ploug, Professor and PhD

Lecture title: AI ethics

Professor, PhD Thomas Ploug has worked for years in the field of data and AI ethics. His key research interests include citizen rights in relation to data and AI use. He is currently running research projects on AI ethics and AI regulation, and he is heading up the Centre for AI Ethics, Law, and Policy at Aalborg University in Copenhagen. Since April 2024, he has been associated with Halmstad University as a visiting professor.

David Sundemo, Researcher and Physician

Lecture title: The role of the human in AI-driven healthcare

David is a clinically practising physician working in primary care. He also works as a researcher at the Sahlgrenska Academy in Gothenburg. He is one of the co-founders of the PETRA group, a research group focused on general emergent technology and artificial intelligence. His research areas include evaluating and implementing AI-driven medical-technical products, self-monitoring, and large language models. He is also, together with an international team, researching the more philosophical aspects arising from the advent of autonomous, high-performance AI systems, raising questions about the future role of the human clinician in healthcare.

Per Nilsen, Professor

Lecture title: What is implementation in healthcare?

Per Nilsen is a Professor of Implementation Science at Halmstad University and a Professor of Social Medicine and Public Health at Linköping University, Sweden. An economist by training at Stockholm School of Economics, Sweden, Nilsen was responsible for building a research and educational programme on implementation science at Linköping University, including a PhD course which has been running annually since 2011. He is interested in applying concepts and theories from beyond implementation science to better understand the challenges involved in achieving practice change. Nilsen has broad interests and has also authored books on rock artists like Prince, David Bowie, and Iggy and the Stooges.

Lena Petersson, Researcher

Lecture title: What do we mean by information, knowledge, real-world evidence, what is useful data?

Lena’s overall research interest is related to how knowledge and information practices change in a digital society, information transparency, and digitalisation in the healthcare sector. Her current research is focused on understanding the challenges and needs that arise in connection with the implementation of new healthcare information systems in the regions and municipalities, with a specific focus on how existing knowledge from implementation and improvement research can be mobilized to increase the success of AI implementation initiatives in healthcare. A specific interest is to improve the possibilities for information-driven collaborative boundary work between healthcare professionals, AI, and patients to create conditions for sustainable and personalized proactive care. She is also doing research that explores and studies how the transparency offered to patients via eHealth solutions such as Open Notes changes the boundaries within health care.

Helena Linge, Associate Professor­­

Lecture talk: Where technology and clinical expectations meet – on AI and information driven care.

Helena Linge was awarded a PhD in 2006 at Lund University, Sweden, and completed post-doctoral research in New York, covering cell- and molecular biology of infection and immunology. She transitioned her research from preclinical immunology to translational clinical research and its implementation. The settings have spanned pan-European research consortia, a national research infrastructure, and interdisciplinary collaborations. She later moved her research into e-health applications for follow-up after childhood cancer, where she co-founded a medtech startup and served as its CEO. She used health data to improve care, showing that information drivenness aligns with precision medicine. Helena Linge has throughout her career raised awareness of current challenges, driven change, inspired novelty and created opportunities for the greater good, with and without AI. After spending time in the innovation sector, Helena Linge, now an Associate Professor at Lund University, holds a position of strategist at R&D in Region Halland.

Patrik Hidefjäll, Owner of Hidetech Consulting

Lecture title: Market access strategies for digital health innovations

Owner of Hidetech Consulting, providing consulting services in medical device innovation in healthcare, affiliated researcher at KI and employee at Halmstad University 20% with prior experience as medtech marketing/sales manager and market access consultant. Special interest in how to access and transform healthcare with medical product innovation. Experience in business planning, market access consulting, market research and forecasting, clinical evaluation, value-dossier development and health-economic evaluation has given a profound understanding of healthcare and life science markets.

James Barlow, Professor

Lecture title: Commercializing and adopting AI-based healthcare innovations – the UK experience

James Barlow is a Professor of Technology and Innovation Management at Imperial College Business School, UK. He studied at the London School of Economics and Political Science. His work focuses on aspects of innovation in healthcare, from creation to adoption. He is particularly interested in the complex relationship between innovation in health technologies, services and infrastructure. James has led or been involved in many research projects around the world and has extensive experience advising and consulting for government and industry. In January 2024, he became Acting Co-Director of Imperial College’s new Centre for Sectoral Economic Performance (CSEP).

Monika Nair, Post-doctoral Researcher

Lecture title: AI implementation in healthcare

Monika Nair is a post-doctoral researcher at Halmstad University. Monika Nair has worked in the field of digital health for years. Her current research interests include understanding how to accelerate the uptake of AI systems in the healthcare sector. She is taking part in the research project on developing an AI implementation framework and developing and implementing the machine learning algorithm for readmission prediction for heart failure patients.

Héléne Laurell, Senior Lecturer

Lecture title: Navigating Institutional Logics in a Health Innovation Ecosystem Context

Héléne Laurell is a Senior Lecturer in Business Administration at the School of Business, Innovation, and Sustainability at Halmstad University, holding a PhD in International Entrepreneurship. Her research focuses on commercialising and internationalising medical technology innovations, exploring the roles of different healthcare settings and business model innovation processes. She is particularly interested in the roles of diverse ecosystem actors operating under different logics, such as healthcare providers, payers, regulators, patients, or users, and their influence on the adoption process of various types of health innovations. She collaborates interdisciplinary on various research projects within the context of information-driven care. Before her academic career, Héléne Laurell gained professional experience in the pharmaceutical sector.

Amira Soliman, Assistant Professor

Lecture title: Applying AI in Healthcare with different real-world use cases

Amira Soliman is an Assistant Professor of Artificial Intelligence and Machine Learning at Halmstad University, specialising in data science, graph analytics, and federated learning. Her areas of expertise include healthcare informatics, social network analysis, and distributed systems. Before joining Halmstad University, she worked as a postdoctoral researcher at RISE Sweden, researching new algorithms to support the design and implementation of robust and large-scale learning algorithms. She received her Ph.D. in information technology from the Royal Institute of Technology (KTH), where the prestigious Marie Curie Initial Training Networks program in the European Union funded her doctoral studies.

Jens Nygren, Professor

Jens Nygren holds a doctorate in medical science and is Professor of Health Innovation at Halmstad University. His research focuses on change work in relation to people's health and health care operations and organization. The research is mainly conducted through intervention-based co-production initiatives with the support of digital innovations and involving end users, public sector and business stakeholders.

Petra Svedberg, Professor

Lecture title: The power of interdisciplinarity

Petra Svedberg’s research is centered around user involvement, shared decision making and quality improvements in healthcare. The research focuses on questions about how health innovations, in the form of interventions supported by digital services and health data analysis, can be developed, implemented and evaluated to provide healthcare organisations with knowledge and support to achieve high quality of care and improved health outcomes for particular groups.

Mattias Ohlsson, Professor

Lecture title: Information driven care (IDC) research programme

Mattias Ohlsson is a professor of Information Technology at Halmstad University, Sweden, specialising in machine learning and data mining. He is also a professor of Theoretical Physics at Lund University, Sweden, with a specialisation in machine learning for medical diagnostics. Mattias's research interests are centred around machine learning and applications within the healthcare domain. One topic of particular interest is explainable AI, i.e., the challenge of opening up the black-box nature of advanced machine learning algorithms, an area of utmost importance for healthcare applications.