Web: http://arxiv.org/abs/2205.05545

May 12, 2022, 1:11 a.m. | Nima Hatami, Tae-Hee Cho, Laura Mechtouff, Omer Faruk Eker, David Rousseau, Carole Frindel

cs.LG updates on arXiv.org arxiv.org

Clinical outcome prediction plays an important role in stroke patient
management. From a machine learning point-of-view, one of the main challenges
is dealing with heterogeneous data at patient admission, i.e. the image data
which are multidimensional and the clinical data which are scalars. In this
paper, a multimodal convolutional neural network - long short-term memory
(CNN-LSTM) based ensemble model is proposed. For each MR image module, a
dedicated network provides preliminary prediction of the clinical outcome using
the modified Rankin …

arxiv cnn data fusion lstm multimodal patients stroke

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