Adding ELM-inspired textual features to a CNN-LSTM classifier yields an accuracy gain from 94.90% to 97.37% on the COVID19-FNIR dataset, but the result is dataset-specific and the statistical evidence is flawed.
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Advanced Health Misinformation Detection Through Hybrid CNN-LSTM Models Informed by the Elaboration Likelihood Model (ELM)
Adding ELM-inspired textual features to a CNN-LSTM classifier yields an accuracy gain from 94.90% to 97.37% on the COVID19-FNIR dataset, but the result is dataset-specific and the statistical evidence is flawed.