A Medical Decision Support System for Automatic Treatment Plan Generation Using Machine Learning Algorithms
Due to demographic change, health economics is increasingly focused on the quality of life in advanced age and the associated cost aspects. Dementia is one of the key issues in this area and its efficient treatment will become increasingly relevant in the near future. Our system aims to automatically create treatment plans for dementia patients in a digital platform. To this end, three algorithms were implemented: a rule-based approach, an approach based on artificial neural networks, and an approach using large language models. A comprehensive synthetic dataset with fictitious patients, medical problems, and treatments was created for training and evaluation of the algorithms.
Authors
- Markus Schinle (ORCID: https://orcid.org/0000-0002-3132-0280)
- Marius Gerdes (ORCID: https://orcid.org/0000-0002-6555-0199)
- Ralf Petzold (ORCID: https://orcid.org/0000-0002-8033-8858)
- Florian Mazura
- Simon Stock (ORCID: https://orcid.org/0000-0001-8326-9758)
- Wilhelm Stork (ORCID: https://orcid.org/0000-0003-0579-4615)
Institutions
- Karlsruhe Institute of Technology (DE)
- FZI Research Center for Information Technology (DE)
- Center for Information Technology (US)
- Offenburg University of Applied Sciences (DE)
Publication Details
- Journal
- Studies in health technology and informatics
- Published
- 2025-05-15
- DOI
- https://doi.org/10.3233/shti250284
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00