Venue: Lecture Hall N2045 (Faculty of Applied Computer Science)

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Abstract

Ever since the publication of ChatGPT, natural language processing (NLP) and large language models (LLM) are popular topics everybody has at least heard about.
Interestingly, there was not much development and interest in the German clinical community until this recent development (same as digitalisation in general). Now, everybody wants to be the first in utilising this (more or less) new technique. However, most of the datasets and models available are focused on English and the adaption to German or other languages and dialects is not a trivial task.
This talk will give an overview about the challenges and possible solutions in German clinical language processing, as well as the potentials and risks of recent developments in NLP research.

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Speaker: Luise Modersohn, M.Sc. (Institute for AI and Informatics of 威尼斯赌博游戏_威尼斯赌博app-【官网】icine, TU Munich)

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Short biography

Luise Modersohn studied Bioinformatics in Jena. After completing her Master's degree, she has worked as a research assistant at the Computer Vision Group at the Friedrich Schiller 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Jena for four years. Since 2018, she has been Research Assistant at the JULIE Lab in Jena. Since last year, she is leader of the DIFUTURE Junior Research Group De.xt at the Technical 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Munich. Her research interests are natural language processing with clinical context, hypergraphs and graph theory, bioinformatics and computational biology as well as computer vision and machine learning.

Venue: Lecture Hall N2045 (Faculty of Applied Computer Science)

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Abstract

The detrimental effects of mental stress on human health have been known for decades, and it has now developed into a major concern in our modern society, where it is regarded as a rising problem and an inevitable part of our everyday life. Psychological stress was shown to be separated into two types: acute and chronic. If stress is not recognized early, it can lead to a variety of diseases and major health problems, including hypertension and coronary disease, irritable bowel syndrome, gastroesophageal reflux disease, generalized anxiety disorder, and depression. In this talk, we will mention some experiments for recognizing stress by using unobtrusive wearables in different environments such as laboratory, real-life events and in the wild. Privacy preserving stress recognition approaches will be also explained. We will also talk about methods for alleviating stress and their performances for decreasing stress levels.

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Speaker: Dr. Yekta Said Can (Chair for Human-Centred Artificial Intelligence, 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Augsburg)

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Short biography

Dr. Yekta Said Can is a postdoctoral researcher with a computer engineering background at the Chair of Human-Centered Artificial Intelligence at the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Augsburg. His research mainly focuses on?the areas wearable computing, physiological signal processing, machine learning, stress recognition, document analysis and social signal processing.

Yekta Can completed his PhD 2019 in Stress Detection and Alleviation in Daily Lives at the?Bo?azi?i 威尼斯赌博游戏_威尼斯赌博app-【官网】 in Istanbul. His latest teaching activities included e.g. "Deep Ubiquitous and Wearable Computing for Healthcare" and "Wearable Technology Applications in Healthcare" at the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Augsburg, as well as the lecture "Principles of Artificial Intelligence" at the Bahcesehir 威尼斯赌博游戏_威尼斯赌博app-【官网】 in Turkey.

Venue: Lecture Hall N2045 (Faculty of Applied Computer Science)

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Abstract

A common theme of many science-fiction scenarios is that the physician of the future seems to be able to wirelessly scan a person and determine his or her health status without physical interference. A common theme of today’s diagnostics is the use of invasive procedures, stationary devices, wires, adhesive-based connections, and the associated limitations in flexibility and comfort. At the same time, the development of sensing modalities for unobtrusive sensing is ever increasing, both in the scientific community as well as in the industry. In part, this ever-accelerating development is fueled by the developments in artificial intelligence. In this talk, we will explore how artificial intelligence, in particular machine learning, sensor fusion, and computer vision may be used to extract diagnostic information using cameras and other types of unobtrusive sensors.

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Speaker: Prof. Dr.-Ing. Christoph Hoog Antink (Chair for Artificially Intelligent Systems in 威尼斯赌博游戏_威尼斯赌博app-【官网】icine, TU Darmstadt)

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Short biography

Prof. Christoph Hoog Antink received the M.Sc. in mechanical engineering from the 威尼斯赌博游戏_威尼斯赌博app-【官网】 at Buffalo, USA, in 2011, and the Dipl. Ing. and Dr. Ing. (Ph.D.) degrees in electrical engineering from RWTH Aachen 威尼斯赌博游戏_威尼斯赌博app-【官网】, Germany, in 2012 and 2018, respectively. Until the end of 2020, he was Head of the 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Signal Processing Group at the Chair for 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Information Technology, RWTH Aachen.

Since then, Christoph Hoog Antink is Assistant Professor (tenure track) and Head of KIS*MED (AI Systems in 威尼斯赌博游戏_威尼斯赌博app-【官网】icine Laboratory), TU Darmstadt, Germany. His research interests include unobtrusive sensing of vital signs, sensor fusion, and machine learning in medicine.

Venue: Lecture Hall N2045 (Faculty of Applied Computer Science)

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Abstract

Efforts made to make data findable, accessible, interoperable and reusable (FAIR) have shown to lead to a more sophisticated data stewardship in various scientific disciplines. One positive consequence of a so-called FAIRification process is the increase in data use and reuse, another observed benefit is the reduction of irreproducle scientific results due to more transparency and richer documentation.

In this talk, I will introduce the FAIR principles in detail using examples from our own work at the 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics Lab. We conducted a baseline assessment of the NFDI4Health metadata schema and worked to FAIRify the core data set used for diabetes research in Germany, the SHIP laboratory data set, and biosimulation models. Currently we run a FAIR assessment of the 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics Core Data Set, funded by EOSC. I will highlight the usefulness of making own data FAIR and present a few tools to do so. I will also discuss with you why it is not easy to achieve FAIRness, and we will learn about possible next steps to implement the FAIR principles in the German medical research community at large.

For example, we recommend that key performance indicators be established to adequately evaluate how data FAIRness benefits health research. Future work also involves developing guidelines for researchers in the form of a simple checklist they can follow. You can read more about these topics in our recent scoping review on FAIR data in health care research (https://www.jmir.org/2023/1/e45013).

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Speaker: Prof. Dr.-Ing. Dagmar Waltemath (Chair of 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics and Head of Core Unit Data Integration Center, 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 Greifswald)

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Short biography

Prof. Dagmar Waltemath is a computer scientist with a specialisation on database and information systems. Since December 2018, she holds a professorship of 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics at the 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 in Greifswald, Germany (Institute of Community 威尼斯赌博游戏_威尼斯赌博app-【官网】icine). Since May 2020, she leads the Research Data Integration Center at the 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. The Core Unit Data Integration Center (CU DIZ) supports clinician scientists in all aspects of research data management and develops methods and tools to extract primary care data from different clinical information systems into a standardised, accessible research data infrastructure. They work on concepts to convert clinical data silos into an integrated data pool that can be accessed by clinicians through a data transfer unit.

Dagmar Waltemaths research is focused on data management in biomedicine, data integration across health care providers and provenance of clinical research data items within clinical information systems. Furthermore, she develops methods and tools for model management in computational biology and is actively involved in COMBINE standardisation efforts.

Venue: Lecture Hall N2045 (Faculty of Applied Computer Science)

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Abstract

Deep convolutional neural networks (DCNNs) can be trained to recognize and classify rare genetic disorders based on their characteristic facial features.?GestaltMatcher?is such an AI that learned to construct a clinical face phenotype space (CFPS) in which portrait images can be placed. Distances in between medical images in the CFPS can be used to quantify syndromic similarities. Cluster analysis in that space reveals close proximity of molecular pathway diseases and can, therefore, be used to support "lumping decisions". Furthermore, the pleiotropic genes causing multiple disorders can also result in distinct facial?gestalt. Thus, cluster analysis can also provide evidence for "splitting decisions", that is indication for different pathomechanisms based on?gestalt?analysis.

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Speaker: Prof. Dr. med. Peter Krawitz (Institute for Genomic Statistics and Bioinformatics, 威尼斯赌博游戏_威尼斯赌博app-【官网】 Hospital Bonn)

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Short biography

Prof. Peter Krawitz studied 威尼斯赌博游戏_威尼斯赌博app-【官网】icine and Physics in Munich. He continued his specialization in 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Genetics at Charité Berlin and did a postdoc in Bioinformatics. As a clinician scientist, he was able to identify the disease-causing variants in the gene PIGV in patients with Hyperphosphatasia with Mental Retardation (aka Mabry syndrome) by exome sequencing in 2009. Peter Krawitz contributed to establishing next-generation sequencing protocols in routine health care with a research focus on deep learning methods to analyze medical imaging data.

In 2017 he was appointed a full professor at the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Bonn and established the Institute for Genomic Statistics and Bioinformatics (IGSB).

Venue: Large Lecture Hall (2nd floor, Room 047, 威尼斯赌博游戏_威尼斯赌博app-【官网】 Hospital)

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Abstract

Clinical decision support tools with artificial intelligence (AI) technologies could synthesize the abundance of data collected in hospitals to help clinicians in identifying which patients may need specific attention and steer additional mental health resources to those at high risk. However, methodological and implementation challenges, such as algorithmic fairness and generalizability, deserve further attention when developing AI-tools within the (mental) healthcare domain. In this talk, we will address the potential and pitfalls for developing responsible AI for mental healthcare.

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Speaker: Assistant Professor Anne de Hond (Department of 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Statistics and Bioinformatics, 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】ical Centre?Utrecht)

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Short biography

Anne de Hond is an assistant professor in the data science program of the 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】ical Center Utrecht. She completed a master's degree in econometrics and worked as a data scientist and researcher in the AI-team at the Leiden 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】ical Center during her PhD studies, where she developed and implemented several AI algorithms. Her research focuses on the responsible development, validation, and implementation of AI algorithms in healthcare. Amongst other applications, she collaborated with Stanford 威尼斯赌博游戏_威尼斯赌博app-【官网】 to develop an AI model to predict depression risk in cancer patients. Her current research interests include validation methods for clinical AI, including large language models like ChatGPT, as well as explainability and fairness of AI algorithms.

Venue: Lecture Hall N2045 (Faculty of Applied Computer Science)

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Abstract

Mobile out-of-the-lab monitoring of electrophysiology data is increasingly in the focus for applications like sports science, brain computer interfacing, neurofeedback, or continuous self-optimization. In this talk, we will discuss technological and methodological requirements as well as selected solutions of state-of-the-art sensors and signal processing methods. We will discuss the impact of mobile recording conditions in the light of the progress of wearable multichannel device development for real-life self-applied use.

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Speaker: Jun.-Prof. Dr.-Ing. Patrique Fiedler (Institute of Biomedical Engineering and Computer Science, TU Ilmenau)

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Short biography

Jun.-Prof. Patrique Fiedler studied electrical engineering and information technology at the Technical 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Ilmenau and received his PhD in biomedical engineering in 2017. He then moved to industry from 2017 to 2021 and took on various development, project and product management activities at an internationally active medical technology manufacturer. Additionally, Patrique Fiedler was a visiting scientist at the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Porto in Portugal and the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Pescara-Chieti in Italy on several occasions.

Since 2021, Patrique Fiedler is a junior professor and head of the department "Data Analysis in Life Sciences" at the Institute of Biomedical Engineering and Computer Science of the Faculty of Computer Science and Automation at the TU Ilmenau. His research topics include data fusion and analysis of multimodal data sets and body sensor networks, as well as the exploration of novel sensor concepts for biomedical engineering. Another focus is the development of online-capable analysis methods for hardware-related data processing.

Venue: Large Lecture Hall (2nd floor, Room 047, 威尼斯赌博游戏_威尼斯赌博app-【官网】 Hospital)

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Abstract

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Speaker: Univ.-Prof. Dr. Oliver Kimberger (Department of Anaesthesia, Intensive Care 威尼斯赌博游戏_威尼斯赌博app-【官网】icine and Pain 威尼斯赌博游戏_威尼斯赌博app-【官网】icine, 威尼斯赌博游戏_威尼斯赌博app-【官网】ical 威尼斯赌博游戏_威尼斯赌博app-【官网】 Vienna)

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Short biography

Prof. Oliver Kimberger is a postdoc consultant anaesthesiologist. He completed a postgraduate course in Statistics and Biometrics at the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Heidelberg (MSc) and an MBA in Health Care Management at 威尼斯赌博游戏_威尼斯赌博app-【官网】Uni Vienna. He also spent a two-year study placement at the Inselspital 威尼斯赌博游戏_威尼斯赌博app-【官网】 Hospital in Berne (Switzerland).

Kimberger is the director of trauma anaesthesia and works as Deputy Head of the Division of General Anaesthesia and Intensive Care 威尼斯赌博游戏_威尼斯赌博app-【官网】icine of the 威尼斯赌博游戏_威尼斯赌博app-【官网】ical 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Vienna.

At the 威尼斯赌博游戏_威尼斯赌博app-【官网】ical 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Vienna, he is also the director of the department’s Data Science group, which is attached to both the Division of General Anaesthesia and Intensive Care 威尼斯赌博游戏_威尼斯赌博app-【官网】icine and the Ludwig Boltzmann Institute for Digital Health and Patient Safety which is hosted by the Division of Anaesthesia and Intensive Care 威尼斯赌博游戏_威尼斯赌博app-【官网】icine of the Department of Anesthesia, Critical Care and Pain 威尼斯赌博游戏_威尼斯赌博app-【官网】icine of 威尼斯赌博游戏_威尼斯赌博app-【官网】Uni Vienna and Vienna General Hospital.

He is a member of the Austrian Society of Anaesthesiology, Resuscitation and Emergency 威尼斯赌博游戏_威尼斯赌博app-【官网】icine and of the European Society of Anaesthesiology. His research interests include topics such as microcirculation & fluid management, patient temperature management, Big Data, Artificial Intelligence and the digital transformation of medicine.

Venue: Lecture Hall N2045 (Faculty of Applied Computer Science)

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Abstract

Epigenetic mechanisms play a crucial role in establishing and preserving cellular states and function throughout an organism’s life. DNA methylation is an essential part of this multilayered regulation and displays a highly conserved, characteristic bimodal distribution across most somatic cell types. For yet unknown reasons, the distribution of DNA methylation is fundamentally different tumors, an intermediate gain of DNA methylation at certain CpG islands and a partial loss of methylation across gene-poor regions. These two features make DNA methylation an ideal readout for tumor-type prediction from sequencing data.

Specifically in the field of neuropathology, DNA methylation-based tumor type classification has recently become part of the WHO. However, even though the field aimed to achieve an intraoperative differential diagnosis for decades, accomplishing this within a clinically relevant timeframe has remained elusive.

Recent advances in third-generation sequencing technologies have brought this goal within reach. To allow for intraoperative CNS tumor type classification within less than one hour, we developed MethyLYZR, a Na?ve Bayesian framework enabling live classification of cancer epigenomes using fully tractable single-CpG resolution modeling while avoiding the need for feature selection or ad hoc model training. MethyLYZR can be run in parallel to an ongoing Nanopore experiment with negligible computational cost and provides clinically relevant and accurate cancer classification results within 15 minutes of sequencing (94% accuracy).

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Speaker: Dr. Helene Kretzmer (Department of Genome Regulation, Max Planck Institute for Molecular Genetics Berlin)

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Short biography

Dr. Helene Kretzmer did her PhD in Bioinformatics at the 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Leipzig, where she focused on the development of methods for DNA methylation sequencing analysis and their application on cancer data in the framework of the International Cancer Genome Consortium. Her main interest is the establishment and stabilization of cell fates. Currently, she is studying how epigenetic factors regulate early mammalian embryonic development using scRNAseq and WGBS data and is also analyzing the epigenetic footprint of cancer to better understand the underlying molecular mechanisms. Helene Kretzmer joined Alex's group in late 2017.

Venue: Large Lecture Hall (2nd floor, Room 047, 威尼斯赌博游戏_威尼斯赌博app-【官网】 Hospital)

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Abstract

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Speaker: Dr. Naveed Ishaque (Scientific Group Leader for Computational Oncology, Berlin Institute of Health and Charité)

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Short biography

Dr. Naveed Ishaque obtained a M.Sc. in Bioinformatics and Systems Biology at Imperial College London and undertook his Ph.D. under Jonathan Jones at Sainsbury Laboratory in Norwich, focusing on the genetic basis of plant-pathogen interactions. As for his post doc, he joined the Heidelberg Centre for Personalised 威尼斯赌博游戏_威尼斯赌博app-【官网】icine under Benedikt Brors and Roland Eils in 2013. In 2018, he moved with Roland Eils to Berlin where he leads the Computational Oncology research group?at the Berlin Institute of Health. His group develops and apply bioinformatics methods for analysing omics data for human diseases, with a strong interest in spatial omics.

Venue: Lecture Hall N2045 (Faculty of Applied Computer Science)

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Abstract

Electrical sensors are used for many neurological or cardiological examinations. Here this is referred to as electroencephalography (EEG) or electrocardiography (ECG). For this purpose, electrodes are placed over the chest or on the head and electrical voltages are measured. This works quite well, but the propagation from the sources (the heart or the brain) to the sensors usually follows very "unusual" (material-dependent) paths. Alternatively, newly developed magnetic sensors can be used - here propagation takes place in a way that is noticeably more "material-independent" for most people. Due to the magnetic measurements, it might be possible in the future to perform much more accurate medical analyses, even without body contact - similar to the "tricorder" from "Star Trek".

In this talk, the Collaborative Research Center 1261 (Magnetoelectric Sensors: From Composite Materials to Biomagnetic Diagnostics), which deals with the research of novel magnetoelectric sensor systems, will be presented first. Then, some of the sensor principles designed to measure low-frequency, extremely weak magnetic fields in typical environments, i.e., without magnetic shielding and without expensive cooling systems, are presented. A brief outlook on biomedical applications for these types of sensors concludes the talk.

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Speaker: Prof. Dr.-Ing. Gerhard Schmidt (Institute for Electrical and Information Engineering, Kiel 威尼斯赌博游戏_威尼斯赌博app-【官网】)

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Short biography

Prof. Gerhard Schmidt received his diploma in electrical engineering from the Technical 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Darmstadt in 1996 and his Ph.D. on signal processing in 2001.?He then worked as a researcher and group leader at Harman/Becker Automotive Systems in Ulm. From 2009 to 2010 he was head of the "Acoustic Speech Enhancement" department of SVOX in Ulm, Germany, as well as Industry Professor (part-time W3) at the Technical 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Darmstadt.

Since 2010, he has been Professor of Digital Signal Processing and Systems Theory at Christian Albrechts 威尼斯赌博游戏_威尼斯赌博app-【官网】 in Kiel.?His research interests include speech and audio processing, medical signal processing, and signal processing for underwater applications.

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Venue: Large Lecture Hall (2nd floor, Room 047, 威尼斯赌博游戏_威尼斯赌博app-【官网】 Hospital)

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Abstract

Translational informatics plays a crucial role in transforming biomedical research, with a special emphasis on the sharing and reuse of data. This talk will present an overview of informatics research at the Berlin Institute of Health at Charité - Universit?tsmedizin Berlin. It will proceed to outline Charité's local strategies and expand to address regional and national infrastructures and platforms in Germany.

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Speaker: Univ.-Prof. Dr. Fabian Prasser (Head of 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics Group, Charité - Berlin 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)

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Short biography

Prof. Fabian Prasser was born in 1982 in Starnberg and studied computer science with a minor in theoretical medicine at the Technical 威尼斯赌博游戏_威尼斯赌博app-【官网】 of Munich. He completed his interdisciplinary doctoral thesis both at the Institute for 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics, Statistics and Epidemiology and in computer science at the Chair for Database Systems. In doing so, he dealt with modern methods of data integration for translational medical research. Another focus of his work is data protection, which he also examined in his habilitation thesis. Fabian Prasser received several awards for his work on data anonymisation, including the Johann Peter Sü?milch 威尼斯赌博游戏_威尼斯赌博app-【官网】al of the German Society for 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Informatics, Biometry and Epidemiology in 2017. Until his move to the Charité, Fabian Prasser was technical coordinator of the consortium "Data Integration for Future 威尼斯赌博游戏_威尼斯赌博app-【官网】icine (DIFUTURE)" in the medical informatics initiative of the Federal Ministry of Education and Research.