HIDA Lectures @ HIDSS4Health
Speaker: Axel Loewe, Karlsruhe Institute of Technology (KIT)
Date: 20.11., 11:00 am
Title: Synergies between mechanistic and data-driven models in medical research
Despite significant advances in machine learning, its application in medicine remains limited. The "big data but small data" paradox highlights key challenges: data are often inaccessible due to legal, ethical, or technical constraints, and lack standardization and curation. High-quality, large-scale labeled datasets are often missing, and biased datasets raise concerns about data coverage and fairness in algorithms.
This lecture will explore how computational modeling and mechanistic simulations can address these challenges by integrating with machine learning. We will present a mechanistic multiscale model of heart electrophysiology, discuss large-scale generation and validation of synthetic data like ECG signals, and examine cases where synthetic data enhanced or replaced real data in training machine learning models.
Axel Loewe
Dr. Axel Loewe is heading the Computational Cardiac Modeling Group at Karlsruhe Institute of Technology in Germany. He is an electrical engineer specialized on biomedical engineering and his research revolves around the development and use of mathematical models of cardiac function including electrophysiology and biomechanics.
