Ekaterina Kutafina (Dr., Dr. rer. medic.)
Biography
I hold two doctoral degrees: in mathematics (AGH University of Science and Technology, Krakow, Poland) and in theoretical medicine (Uniklinik RWTH Aachen, Aachen, Germany). My expertise lies in developing comprehensive pathways to provide computational support for collaborative and integrative medical research. I translate medical questions into computational terms and build mathematical models, including AI-based decision systems. For many years, I have been working on analysis of the data from medical sensors and wearable devices, in the areas of neurology, psychiatry, and physiology, particularly epilepsy and neuropathic pain. At BI-K, I lead the strategic research direction of data-driven medicine, emphasizing FAIR data integration and optimizing data flows for interdisciplinary research. Additionally, as an EOSC (European Open Science Cloud) expert for Open Scholarly Communication, I advocate for open science and publishing of scientific artifacts beyond manuscripts. Finally, I am researching and teaching methodologies necessary for successful transdisciplinarity collaborations in computational medicine.
Contact
- Email ekaterina.kutafina@uni-koeln.de
- Office mail: Kerpener St. 62 - 50937 Köln visiting: BI-K - Geb. 705 - Zülpicher Str. 58e - 50672 Köln - 1 OG - Room 1.007
- Google Scholar
- Digital C Fiber
Academic Background
Areas of Expertise
Research Focus
- Computational Medicine
- Time-series Physiological Data
- Digital Human Twins
- Neuroscience of Pain
- Transdisciplinarity
- Medical Data Science
Current Teachings
Kolloquium "Advances in Biomedical Informatics Research: Graduate Students"
[Diese Lehrveranstaltung wird nur auf Englisch angeboten] The colloquium is aimed primarily at masters and doctoral students, researchers, and scientific personnel of the biomedical Informatics Institute. The co-supervised students from other clinics or research institutions in biomedical informatics and medical data science can also enroll. Students will be mentored and will present the outcomes of their ongoing research, or will review an article from a peer-reviewed journal.
Show in KLIPSStudium Integrale: Interdisciplinary collaboration for digital solutions
Medical AI - From basics to pro: Heart Rate Variability & AI symbiosis in personalized medicine
[Diese Lehrveranstaltung wird nur auf Englisch angeboten] Heart rate variability (HRV) is widely used in clinical settings as a non-invasive autonomic nervous system function marker. It helps assess cardiovascular health, stress levels, and overall well-being. Clinicians use HRV to monitor conditions like heart disease, hypertension, and diabetes, as well as to evaluate recovery in post-surgical and critically ill patients. HRV also plays a role in mental health, aiding in the diagnosis and management of anxiety, depression, or PTSD. Additionally, it is used in sports medicine and rehabilitation to track recovery and optimize training. Its broad applications make it a valuable tool in personalized medicine. The development of AI methods allows to make more complex predictions using multiple HRV parameters simultaneously. This complexity enabled successful decision support in the domains where HRV was not previously prominent for clinical use, such as epileptology. In this lecture block, we will discuss the technical aspects of HRV assessment, such as different sensors, data quality control or different HRV measures. We will review various types of clinical applications, but also the ¿citizen science¿ approach and sports coaching. For the practical part we take a dataset with precomputed R-to-R intervals and different labels (e.g. RR Interval Time Series Modeling: The PhysioNet/Computing in Cardiology Challenge 2002 v1.0.0 ). We will test different machine learning approaches to classify the data, e.g. to detect whether the data was recorded in a stressed or relaxed phase. This block lecture does not require any previous coding experience, we will use the graphical low-code platform KNIME. Students are required to bring their own laptop.
Show in KLIPS
