The medical informatics funding concept provides for increased training of young scientists in the data sciences. Digitization and medicine are rapidly growing fields of knowledge whose interfaces are leading to fundamental changes in healthcare and opening up new possibilities for patients in diagnostics, therapy and prevention. The basis of this digitization is medical data. In order to use the growing amounts of data in medicine in a meaningful way, digital competencies are needed in healthcare. By establishing new professorships, the SMITH Consortium is providing sustainable support for both research and teaching in medical informatics.
Dr. Jan Christoph was awarded the new junior professorship “Biomedical Data Science” at the University Medicine Halle (Saale) on 1 May, 2021. It deepens the profile in the field of medical informatics and data-based medical research. In addition, the junior professorship is accompanied by the scientific management of the Data Integration Center (DIC). This is being established by Halle University Medical Center, a partner of the SMITH Consortium, as part of its participation in the Medical Informatics Initiative (MII) of the German Federal Ministry of Education and Research (BMBF).
The working group of the professorship focuses on IT infrastructures for translational research. Two PhD students, supported by scientifically oriented staff at the Data Integration Center, develop methods for the acquisition and integration of clinical research data and for accompanying research data management. Furthermore, the use of systems for clinical decision support is scientifically supported, e.g. in the context of SMITH use cases or the molecular tumor board of the Krukenberg Cancer Center Halle (KKH).
The research focus of the University Medical Center Halle will thus be further strengthened in the areas of epidemiology and healthcare research as well as molecular medicine and signal transduction, especially in the fields of cardiovascular diseases and cancer.
The Institute for Digital Medicine at Bonn University Hospital, headed by Prof. Dr. Stephan Jonas, was established in summer 2021. The new professorship will conduct research into how medically relevant patient data can be digitally collected, analysed and made usable for studies or clinical processes. One research focus at the institute is the use of smartphones and wearables, small computer systems worn on or near the body. These systems can collect data in the background that describe the physical or mental state of the user. As digital phenotypes, the everyday data obtained in this way can help in the long term to generate early indicators for diagnoses or to offer personalized treatments that achieve the optimal outcome for the respective lifestyle.
In cooperation with the SMITH Consortium, a Data Integration Center is being established at the University Hospital of Bonn to anonymize healthcare data and make it usable for biomedical research. As a SMITH partner, the University Hospital Bonn is also participating in the clinical Use Case ASIC.
Prof. Dr. Toralf Kirsten was appointed to the professorship for Medical Data Science jointly established by the Medical Faculty of the Leipzig University and the Leipzig University Medical Center on August 1, 2021. The professorship aims to develop and establish infrastructural components as well as to evaluate medical data collected and processed as part of the Medical Informatics Initiative at the Leipzig University Medical Center. This is intended to provide scientific support for the Data Integration Center of the Leipzig University Medical Center on the one hand and to create a link to clinical and epidemiological scientists on the other. At the same time as the professorship, the Medical Data Science Department was created at Leipzig University Medical Center, which is headed by Prof. Kirsten.
The current infrastructural challenges of the professorship include the development and establishment of a distributed analysis infrastructure with which data from different university hospitals can be analysed without the individual data of the patients leaving the hospital. The professorship works closely with the Fraunhofer Institute for Applied Information Technologies and the University of Cologne.
In addition, the professorship cooperates very closely with the Institute of Medical Informatics, Statistics and Epidemiology of the Leipzig University and the Center for Scalable Data Analytics and Artificial Intelligence Dresden Leipzig (ScaDS.AI). The former has been involved in the analysis of clinical and epidemiological data for years, while ScaDS.AI focuses primarily on basic and application-oriented research for Big Data and Artificial Intelligence (AI). The cooperation makes it possible to apply current AI methods and procedures in medical research and to communicate new challenges directly to both centers. The focus of the Leipzig University Medical Center will thus be further strengthened, especially with regard to the evaluation of clinical data.
Prof. Dr. Folker Meyer
Professor for Data Science | Essen University Hospital
Prof. Dr. Folker Meyer has held the chair for Data Science at the Institute for Artificial Intelligence in Medicine (IKIM) of the University Hospital Essen at the University of Duisburg-Essen since 2020.
In addition to the data science methods, formerly called Big Data, bioinformatics and genome research methods are used. The Data Science professorship aims to add the use of microbiome and virome data to improve medium-term patient care. The research group develops new methods for the preparation, integration and analysis of sequencing data, thereby covering the entire process.
Combined with a data science approach, virome and microbiome analyses provide important clues for detecting infections. For example, the analyses make it possible to set up a surveillance mechanism to detect emerging DNA and RNA pathogens or antibiotic resistance at an early stage.
In general, the rapid molecular characterization of infectious diseases can be helpful for the early detection of life-threatening diseases such as sepsis or necrotizing enterocolitis (NEC), an inflammatory bowel disease that primarily affects premature infants. The junior research group SepsisPrep is specifically dedicated to sepsisprediction in intensive care patients.
Prof. Dr. Cord Spreckelsen
Professor of Medical Informatics at the Institute of Medical Statistics, Computer Science and Data Sciences (IMSID) | University Hospital Jena
The professorship for medical informatics at Jena University Hospital aims to improve the use of data from patient care. It serves as a bridge between informatics, medical research, teaching and operational hospital IT.
The working group of the professorship develops and researches methods for the processing, evaluation and algorithmic use of health care data. Focal points are: approaches to improve data integration through ontologies, methods for data protection, including the use of distributed, privacy-friendly machine learning and methods for medical knowledge processing and decision support. The research group is working on combining data-driven artificial intelligence (AI) with logic-based AI in medicine. One application focus is the analysis and AI-supported prediction of consumption quantities, material flows and utilization figures in hospital operations. The goal here is to improve resource and process planning. Another application focus is the use of artificial intelligence to increase data quality.
An additional field of activity of the professorship is the development of suitable digital teaching formats for the effective teaching of medical informatics competencies. The focus here lies on the promotion of multiprofessional collaboration in the healthcare sector, explicitly including IT experts and AI systems. The field of activity includes the implementation of studies on educational research as well as technical development.
Prof. Dr. Frank Ückert leads the Institute for Applied Medical Informatics at the University Medical Center Hamburg-Eppendorf and brings together complex medical data with his team. In cooperation with experts in medical informatics and related disciplines, new knowledge is being generated that will allow diseases to be better understood and patients to be treated more successfully in the future. Furthermore, innovative processes as well as customized methods and tools for physicians and researchers are developed and published.
The goal is to make heterogeneous data sets available for medical research, to enable interdisciplinary and international collaborations, and to simplify complex analyses. The institute maintains project groups on applied AI, agile system development, data management, data annotation and visualization.