Web: http://arxiv.org/abs/2206.08019

June 17, 2022, 1:13 a.m. | Meiyan Huang, Tao Wang, Xiumei Chen, Xiaoling Zhang, Shuoling Zhou, Qianjin Feng

cs.CV updates on arXiv.org arxiv.org

Longitudinal variations and complementary information inherent in
longitudinal and multi-modal data play an important role in Alzheimer's disease
(AD) prediction, particularly in identifying subjects with mild cognitive
impairment who are about to have AD. However, longitudinal and multi-modal data
may have missing data, which hinders the effective application of these data.
Additionally, previous longitudinal studies require existing longitudinal data
to achieve prediction, but AD prediction is expected to be conducted at
patients' baseline visit (BL) in clinical practice. Thus, we …

alzheimer's arxiv attention cross data disease imputation network on prediction

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