Suchergebnisse - "Relevance factor variational autoencoder"

Developing a fair and interpretable representation of the clock drawing test for mitigating low education and racial bias von Zhang, Jiaqing, Bandyopadhyay, Sabyasachi, Kimmet, Faith, Wittmayer, Jack, Khezeli, Kia, Libon, David J., Price, Catherine C., Rashidi, Parisa

“… The clock drawing test (CDT) is a neuropsychological assessment tool to screen an individual’s cognitive ability. In this study, we developed a Fair and …”
Volltext

Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands von Bandyopadhyay, Sabyasachi, Wittmayer, Jack, Libon, David J., Tighe, Patrick, Price, Catherine, Rashidi, Parisa

“… In this study, we used the relevance factor variational autoencoder (RF-VAE), a deep generative neural network, to represent digitized clock drawings from multiple institutions using an optimal number of disentangled latent factors …”
Volltext

A vision transformer approach for fully automated and scalable dementia screening using clock drawing test images von Bone, Michael B., Freedman, Morris, Black, Sandra E., Felsky, Daniel, Kumar, Sanjeev, Pugh, Bradley, Strother, Stephen C., Tang‐Wai, David F., Tartaglia, Maria Carmela, Buchsbaum, Bradley R.

“… ‐scored features (74.3%) and existing deep learning models (MiniVGG = 73.3%, MobileNetV2 = 72.3%, relevance factor variational autoencoder …”
Volltext

FaIRClocks: Fair and Interpretable Representation of the Clock Drawing Test for mitigating classifier bias against lower educational groups von Zhang, Jiaqing, Bandyopadhyay, Sabyasachi, Kimmet, Faith, Wittmayer, Jack, Khezeli, Kia, Libon, David J, Price, Catherine C, Rashidi, Parisa

“… We represented clock drawings with a 10-dimensional latent embedding using Relevance Factor Variational Autoencoder (RF-VAE …”
Weitere Angaben