论文标题
多因素骨时代预测的不确定性估计的变异推理和贝叶斯CNN
Variational Inference and Bayesian CNNs for Uncertainty Estimation in Multi-Factorial Bone Age Prediction
论文作者
论文摘要
除了在临床医学中广泛使用外，法律医学中的生物年龄（BA）还用于评估未知文档的应用中未知年代年龄（CA）。文献中提出的年龄估计的自动方法正在预测点估计，而无需量化预测性不确定性，这可能会产生误导。在MRI数据中的多因素年龄估计方法中，我们使用了变异推理方法来估计贝叶斯CNN模型的不确定性。区分模型的不确定性与数据不确定性，我们将数据不确定性解释为生物学变异，即具有相同BA的受试者的CA范围。
Additionally to the extensive use in clinical medicine, biological age (BA) in legal medicine is used to assess unknown chronological age (CA) in applications where identification documents are not available. Automatic methods for age estimation proposed in the literature are predicting point estimates, which can be misleading without the quantification of predictive uncertainty. In our multi-factorial age estimation method from MRI data, we used the Variational Inference approach to estimate the uncertainty of a Bayesian CNN model. Distinguishing model uncertainty from data uncertainty, we interpreted data uncertainty as biological variation, i.e. the range of possible CA of subjects having the same BA.
