Plenary speech 1:

Title: Why Bump Reward Function Works Well In Training Insulin Delivery    Systems             

Vladik Kreinovich

 Professor of University of Texas at El Paso, USA

(Co-authors: Lehel Denes-Fazakas, Laszlo Szilagyi, Gyorgy Eigner, Olga Kosheleva, Vladik Kreinovich, and Hoang-Phuong Nguyen)


Diabetes is a disease when the body can no longer properly regulate blood glucose level, which can lead to life-threatening situations. To avoid such situations and regulate blood glucose level, patients with severe form of diabetes need insulin injections. Ideally, the system should automatically decide when best to inject insulin and how much to inject. To find the optimal control, researchers applied machine learning with different reward functions. It turns out that the most effective learning occurred when they used the so-called bump function. In this paper, we provide a possible explanation for this empirical result.


Vladik Kreinovich is Professor of Computer Science at the University of Texas at El Paso. His main interests are representation and processing of uncertainty, especially interval computations and intelligent control. He has published 13 books, 39 edited books, and more than 1,800 papers.

Vladik is Vice President of the International Fuzzy Systems Association (IFSA), Vice President of the European Society for Fuzzy Logic and Technology (EUSFLAT), Fellow of International Fuzzy Systems Association (IFSA), Fellow of Mexican Society for Artificial Intelligence (SMIA), Fellow of the Russian Association for Fuzzy Systems and Soft Computing.

Plenary Speech 2:

Title: Knowledge Management for Clinical Decision Support—Synopsis and Future
Professor Klaus-Peter Adlassnig

Institute of Artificial Intelligence, Medical University of Vienna, Austria &

Medexter Healthcare, Vienna, Austria

Abstract: Clinical decision support (CDS) is – by definition and in its simplest form – the application of clinical knowledge to patient medical data. Various forms of CDS have been proposed and realized. They range from early approaches to computer-aided diagnosis and therapy, to machine learning and medical expert systems, to easily accessible and well-organized textual sources of abstracted and summarized medical publications. More modern dimensions include machine learning based on “Big Data” images and texts, purpose-built computable biomedical and clinical knowledge, and finally, most recently, CDS with large language models (LLMs) such as ChatGPT and others.
CDS approaches rely on many different forms of clinical knowledge and its management. This talk will provide an overview of current approaches and go into more details about current knowledge management with LLMs.

2012 at HL7 Meeting in
Vancouver, Canada, © Ken Rubin
Curriculum vitae

Klaus-Peter Adlassnig, PhD, MSc, FACMI, FIAHSI
Professor of Medical Informatics (retired)
former Head of the Section for Medical Expert and Knowledge-Based Systems
(now Section for Artificial Intelligence and Decision Support)
Center for Medical Statistics, Informatics, and Intelligent Systems Medical University of Vienna, Austria
Spitalgasse 23, A-1090 Vienna, Austria
tel.: +43-1-40400-66680; fax: +43-1-40400-66250
Medexter Healthcare GmbH
CEO and Scientific Head
Borschkegasse 7/5, A-1090 Vienna, Austria
tel.: +43-1-9680324; fax: +43-1-9680922

Klaus-Peter Adlassnig received his MSc degree in Computer Science from the Technical University of Dresden, Germany, in 1974. He joined the Department of Medical Computer Sciences of the University of Vienna Medical School, Austria, in 1976. In 1983, he obtained his PhD degree in Computer Sciences from the Technical University of Vienna, Austria, with a dissertation on “A Computer-Assisted Medical Diagnostic System Using Fuzzy Subsets”.

Dr. Adlassnig was a postdoctoral research fellow with Professor Lotfi A. Zadeh at the Computer Science Division at the Department of Electrical Engineering and Computer Sciences of the University of California at Berkeley, U.S.A., from 1984–86. He received his Venia docendi for Medical Informatics from the University of Vienna in 1988 and became Professor of Medical Informatics in 1992. In 1987, he received the Federal State Prize for excellent research in the area of rheumatology, awarded by the Austrian Federal Ministry for Health and Environmental Protection. From 1988–2015, he was head of the Section on Medical Expert and Knowledge-Based Systems at the Department of Medical Computer Sciences of the University of Vienna Medical School (now: Section for Artificial Intelligence and Decision Support at the Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna). In 2014, he has been elected to Fellow of the American College of Medical Informatics (ACMI), and in 2018 to Fellow of the International Academy of Health Sciences Informatics (IAHSI).

Prof. Adlassnig was a Visiting Professor at the Department of Medicine, Section on Medical Informatics, at the Stanford University Medical Center, U.S.A., in summer 1993, and a guest lecturer and guest professor at the Department of Electrical and Biomedical Engineering in the Technical University of Graz, Austria, from 1994 to 2004. He spent the summer 2000 as a visiting scholar at the Department of Electrical Engineering and Computer Sciences, Computer Science Division, Berkeley Initiative in Soft Computing (BISC), University of California, Berkeley, U.S.A., May 2005 as guest researcher at the Department of Computer Science, Meiji University, Kawasaki, Japan, and September 2008 as visiting scientist at the Clinical Decision Making Group, Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), Cambridge/U.S.A.

From 2002 to 2016, Prof. Adlassnig was the Editor-in-Chief of the International Journal “Artificial Intelligence in Medicine”, Elsevier Science Publishers B.V., and was the director of the Ludwig Boltzmann Institute for Expert Systems and Quality Management in Medicine from 2002 until 2005. He is co-founder, CEO, and Scientific Head of Medexter Healthcare GmbH (, a company established to broadly disseminate intelligent medical systems with clinically proven usefulness. Since its inception in 2002, Medexter succeeded in establishing technical platforms and clinical decision support systems for a number of academic, commercial, and clinical institutions.

Prof. Adlassnig’s research interests focus on computer applications in medicine, especially medical expert and knowledge-based as well as clinical decision support systems and their integration into medical information and web-based health care systems. Prof. Adlassnig is highly interested in formal theories of uncertainty, particularly in fuzzy set theory, fuzzy logic, fuzzy control, and related areas. He is equally interested in the theory and practice of computer systems in medicine. Prof. Klaus-Peter Adlassnig’s sphere of interest includes various aspects of the philosophy of science, particularly the state and future impact of artificial intelligence.

Plenary Speech 3