… deep learning in biological age estimation. We consider the current data modalities that have
been used to study aging and the deep learning … of algorithms for biological age estimation …

… Given the success of the unsupervised biological age model in our study, we further expect
a development of unsupervised deep learning architectures, such as deep auto-encoders 35 …

… Biological age, a measure of overall health, may improve … to estimate biological age using
a convolutional neural network that takes as input a CXR image and outputs a chest x-ray age (…

… based on deep convolutional long short term memory (ConvLSTM) to predict biological age,
… We also demonstrate five deep biological age estimation models including the proposed …

… we developed a deep learning (DL) algorithm to predict BA based on retinal photographs and
… We developed a retina-based biological age (termed RetiAGE) based on a deep learning …

… , we introduce the concept of biological age. When we casually refer to age, we refer to what
will … We discuss these existing biological age predictors more in detail in the supplemental. …

… We reported the first application of a deep learning algorithm to estimate biological age …
In conclusion, although the proposed deep learning blood-based BA marker needs further …

… We present RSAE, which is an unsupervised deep learning algorithm to estimate BA. Our
undated autoencoder structure composed of a modified loss function to include the RS can …

… biological age. Thus, rather than using 1D CNN [11] to estimate biological age, we apply
a deep learning … of our proposed biological age estimation methods with the existing deep …

… Accelerated biological ageing is a major underlying mechanism of frailty development.
This study aimed to investigate if the biological age measured by a blood biochemistry-based …