Grand Rounds - 26 November 2024 with Matthias Schulte-Althoff

Matthias Schulte-Althoff is a Research Fellow at the Institute for Medical Informatics at Charité Universitätsmedizin Berlin in Germany, in collaboration with the Einstein Center Digital Future. He is currently completing his PhD in Information Systems Research at Freie Universität Berlin. Matthias has a background in computer science and was a visiting scholar at the University of British Columbia in Vancouver. He has received several fellowships, including from the Joachim Herz Foundation, and his scholarly contributions span conferences and journals in both digital health and information systems, reflecting his efforts to advance healthcare through the application of machine learning and data science.

Patient-Centered Interventions: Machine Learning for Comprehensive Fall Risk Assessment

This research explores the potential of interpretable machine learning methods in predicting patient falls. Using over two million electronic health records from a German university hospital (2016-2022), our research uses predictive analytics and localized, explainable AI to create discernible patient risk profiles. The study aims to identify the network of risk factors at both the individual and group patient level, providing a framework for data-driven fall risk assessment. The results will provide insights for the development of clinical decision support systems that enable more accurate preventive care decisions and efficient resource allocation. Specifically, it highlights the importance of nursing data for precision in intervention planning.

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