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

• Main Authors: MANSI TOMMASO, COMANICIU DORIN
• Format: Patent
• Language: Chinese; English
• Published: 09.04.2021
• Subjects: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; PHYSICS

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. 使用患者、患者器官或患者器官系统的数字孪生体模型以用于临床决策支持，可以从该模型中导出生物标志物。个体化过程还包括预测性考虑（16），以改进数字孪生体导出的生物标志物的灵敏度和特异性。特别地，在训练期间，要针对其使用个体化模型的预测性生物标志物被考虑在内（16），然后在应用中计及该生物标志物。针对特定患者的模型的拟合（15）计及（16）预测或模型使用，从而导致估计出（14）针对最终用途更优化的生物标志物，而不是仅仅拟合到患者的当前基线。