Stacked LSTM/BiLSTM networks improve correlation coefficients by up to 27.5% over single LSTM on selected simulated EIT test models, but the result lacks statistical support, code, and clinical validation.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.bio-ph 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Pulmonary electrical impedance tomography based on deep recurrent neural networks
Stacked LSTM/BiLSTM networks improve correlation coefficients by up to 27.5% over single LSTM on selected simulated EIT test models, but the result lacks statistical support, code, and clinical validation.