Veranstaltungsort: Gro?er H?rsaal (2.OG, Raum 047, Universit?tsklinikum)

?

Abstract

I will talk about the application of automated, quantitative image analysis in combination with machine learning and artificial intelligence in radiology. These techniques have the potential to revolutionize clinical routine. I will illustrate how machine learning and artificial intelligence can be used in radiology to solve typical problems, using examples from my research group.

However, there are also challenges and difficulties that can arise when implementing these technologies into clinical routines, such as data issues, and data and computing infrastructure. I will also highlight potential solutions and strategies to address these challenges.

I hope that after my talk, you will have a better understanding of how clinical data science can improve radiological diagnostics and thus have a positive impact on patient care.

?

Referent: Prof. Dr. Michael Ingrisch (Clinical Data Science in Radiology, LMU Klinikum München)

?

Kurzbiographie

I am leading the group for Clinical Data Science at the Department of Radiology. We employ advanced statistics, machine learning and computer vision techniques in the context of clinical radiology to enable fast and precise AI-supported diagnosis and prognostication. Open science and reproducible research in this field is highly relevant, especially with deep learning or machine learning. While it is easy to share analyses and code, the sensitive nature of medical images and associated clinical data poses challenges with respect of public data sharing. I believe the Open Science Center provides the ideal framework to address these challenges.

Current position: W2 Professor for Clinical Data Science in Radiology, Department of Radiology, 威尼斯赌博游戏_威尼斯赌博app-【官网】 hospital, LMU Munich. A selection of scientific activities and memberships:

Since 2022: Fellow of the Konrad Zuse School of Excellence in Reliable AI (relAI).

Since 2021: PI in the Munich Center for Machine Learning (MCML); Member of the focus area “Next Generation AI”, Center of Advanced Studies; Coordinator of the ?Clinical Open Research Engine“(CORE) established as shared, collaborative high performance computing environment at LMU Klinikum (Profs. Ingrisch, Hinske).

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

?

Abstract

Referent: Dr. Thomas Wendler Vidal (Technische Universit?t München)

?

Kurzbiographie

Veranstaltungsort: Kleiner H?rsaal (2.OG, Raum 048, Universit?tsklinikum)

?

Abstract

In this lecture the origin and development of the National Intensive Care Evaluation (NICE) registry, a Dutch quality registry including all ICU patients in the Netherlands will be presented. The lecture will explain which data is included, to what extent it is possible to use routinely collected data from the EHR to fill the NICE registry, and which measures are taken to optimize data quality and reduce administrative burden. The primary aim of the NICE registry is to support ICUs in monitoring and improving quality of care. Benchmarking or audit and feedback, i.e. the strategy that intends to encourage professionals to change their clinical practice by providing professional performance based on explicit criteria or standards back to professionals in a structured manner, is an important strategy of quality registries in realising quality improvement. The lecture will include examples on the effectiveness of audit and feedback, among which an RCT on actionable indicators and a toolbox for improvement activities in the domain of pain management. The secondary aim of the NICE registry is to provide an infrastructure to research medical and methodological medical informatics research questions. If time allows, some examples out of ~180 scientific journal papers and 15 PhD theses based on the NICE registry will be presented.

?

Referentin: Prof. PhD Dr. Nicolette F. de Keizer (Amsterdam Unviersity 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Center)

?

Kurzbiographie

Nicolette de Keizer has a master and PhD in 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics of the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Amsterdam. She has a special interest in reusing routinely collected data to evaluate quality of care and impact of health care information systems. She is one of the founders of the National Intensive Care Evaluation (NICE) quality registry for Dutch intensive care units and of the post-graduate Master Health Informatics. She is appointed Principle Investigator in AmsterdamUMC and full professor of the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Amsterdam. She is chair of the department of 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics, one of the leading 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics departments in the Netherlands. With her department she provides 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics training and research at BSc, MSc and PhD level.

?

Nicolette is internationally recognized as an expert in quality assessment, audit and feedback and standards for data reuse and she acted for years as an expert for the Dutch National ICT institute in health care and the international SNOMED CT quality committee for terminology development and maintenance. She was co-chair of several international medical informatics conferences and workshops. She is chair of the Dutch cooperation of Quality Registries and member of the Dutch data governance committee for quality registries. She supervised 25 graduated and 13 ongoing PhD students and over 40 Bachelor and Master students during scientific research projects. She published over 300 scientific research papers and book chapters, and was co-editor of the book “Applied interdisciplinary theory in health informatics: a knowledge base for practitioners”. Her H-index is 63 (Google Scholar)

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

?

Abstract

This talk gives a short overview on the literature on prognostic and predictive models for patients with Multiple Sclerosis. Besides a methodological overview, I discuss issues on the performance quality of such models and how how they reflect patient interests. Own experience will be reported gained from model development on data available within the DIFUTURE consortium as well as data from the french national MS Registry (OFSEP). At the end, we have to discuss how to cope with a very unsatisfying overall perspective:

Do we need better and more data? Do we need more advanced methods?

Do we need a deeper understanding of the disease?

?

Referent: Univ. Prof. Dr. Ulrich Mansmann (Direktor des IBE, 威尼斯赌博游戏_威尼斯赌博app-【官网】izinische Fakult?t LMU)

?

Kurzbiographie

Prof. Dr. Ulrich Mansmann is head of the Department of 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Information Sciences, Biostatistics, and Epidemiology at the Ludwig-Maximilian’s 威尼斯赌博游戏_威尼斯赌博app-【官网】 Munich. His background is a PhD in Mathematics (1990, Technical 威尼斯赌博游戏_威尼斯赌博app-【官网】 Berlin). In 1991 he started to work as assistant professor at the 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Center of the Free 威尼斯赌博游戏_威尼斯赌博app-【官网】 in Berlin working in Clinical Epidemiology with main focus on clinical trials and prognostic studies. In 2000 he moved to the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Heidelberg and cooperated with colleagues from the German Cancer Center (also located in Heidelberg). He was member of the German National Genome Research Network (NGFN). In January 2005, Prof. Mansmann was invited as head of Department at the Institute of 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Information Science, Biometrics, and Epidemiology (IBE) at the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Munich (LMU). The IBE represents methodological research on a wide spectrum of 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Sciences: Public Health, Epidemiology, Clinical Epidemiology, as well as Molecular 威尼斯赌博游戏_威尼斯赌博app-【官网】icine. This position allowed deepening and extending activities in the fields of research which are at the heart of his interest. Especially, his experiences in prognostic oncological research combined with activities in the field of Bioinformatics as well as clinical trials were helpful to enter the fields of translational medicine as well as personalized medicine. Prof. Mansmann is also spokesman of the LMU’s program in Public Health and Epidemiology.? From 2012 to 2020 he served as a DFG collegiate. Since 2017, Professor Mansmann joins the federal 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics Initiative (MII).

Veranstaltungsort: Gro?er H?rsaal (2.OG, Raum 047, Universit?tsklinikum)

?

Abstract

Digital technologies are changing the field of medicine and health. Ubiquitous medical devices can be used as point-of-care tools to measure and timely deliver personalized medical treatments across the whole continuum of care. However, this comes with a number of technical and medical challenges that will guide the research and development of digital health technologies in the coming years. In this talk I will highlight how medical automation and artificial intelligence can open new avenues to enable easy access to medical technology outside specialized clinical centers, with an example in sleep research. Intelligent user-machine interaction,? automation, and machine learning approaches will have a huge impact on future medical technologies and will find applications in many medical domains, from prevention to treatment.

?

Referent: Prof. Dr. Walter Karlen (Institut für Biomedizinische Technik, Universit?t Ulm)

?

Kurzbiographie

Prof. Walter Karlen is professor for Biomedical Engineering at Ulm 威尼斯赌博游戏_威尼斯赌博app-【官网】 since May 2021 where he specializes in the research on design and algorithms for medical wearables and their applications.

He was a Swiss National Science Foundation professor at the Eidgen?ssische Technische Hochschule Zürich (ETH Zürich) from 2014 to 2020 where he founded and directed the Mobile Health Systems Lab. Between 2005 and 2014, he held research positions at the University of Stellenbosch, South Africa, BC Children's Hospital and Child and Family Research Institute (CFRI), Vancouver, Canada; the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of British Columbia (UBC) in Vancouver, Canada;? and Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Walter Karlen holds a Master degree in micro-engineering from EPFL and a Docteur ès sciences (PhD) in Computer, Communication and Information Sciences (also EPFL).

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

?

Abstract

The research project ?GenoPerspektiv‘ of the UMG (威尼斯赌博游戏_威尼斯赌博app-【官网】 威尼斯赌博游戏_威尼斯赌博app-【官网】icine G?ttingen) focuses on the handling of genomic high-throughput data, taking into account perspectives from the fields of clinical practice, ethics, law, and biomedical information technology. The project aims to address the various challenges and opportunities associated with the use of genomic data in healthcare. Within the realm of medical informatics, Professor Sax is specifically engaged in a subproject that delves into the application of information and health technology in medicine. This entails studying the integration of digital systems and tools to enhance healthcare delivery, data management, and decision support. Therefore, he conducts research on data privacy and security in telematics, with a particular focus on healthcare settings, where he explores the implementation and utilization of electronic patient records and personal health records in translational research. His work aims to optimize the functionality and interoperability of these digital platforms, facilitating seamless information exchange a