SMuK 2023 – wissenschaftliches Programm

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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz

AKPIK 7: AI Topical Day – Research Data Management and Medical Applications

AKPIK 7.5: Vortrag

Donnerstag, 23. März 2023, 15:00–15:15, HSZ/0101

Interpretable Machine Learning and evidence-based decision support in clinical Digital Twins — •Carlos Andres Brandl, Anna Nitschke, and Matthias Weidemüller — Im Neuenheimer Feld 226, 69120 Heidelberg, Germany

Personalized medicine is based on including a vast variety of patient-specific data. The Digital Twin technology provides the opportunity for improved personalized patient care by monitoring the patient journey and predicting the best preventive and therapeutic decision options available. We developed a concept which fuses evidence-based methods with machine learning approaches into a single decision-support tool. Our method is independent on the parameter spaces and evidence-based tools being used, provides possibilities to include updated knowledge and is able to offer intuitively interpretable decision options to the clinician. The presentation introduces our architecture of the digital twin and provides details on the fusion approach.