DATA-DRIVEN ESTIMATION OF PREDICTIVE DIGITAL TWIN MODELS FROM MEDICAL DATA

摘要

Digital twin models of a patient, patient organ, or patient organ system from which biomarkers can be derived are used for clinical decision support. The individualization procedure also includes a predictive consideration (16) to improve the sensitivity and specificity of the digital-twin derived biomarker. In particular, during training, the predictive biomarker for which the individualized model is to be used is taken into account (16), which then accounts for the biomarker in application. The fitting (15) of the model for a specific patient accounts (16) for the prediction or model usage, resulting in estimating (14) biomarkers more optimized for the end use rather than just fit to the current baseline of the patient.