This study introduces a novel CEL model for Continual learning by leveraging domain adaptation via Elastic Weight Consolidation (EWC)(https://arxiv.org/abs/2401.08940). This approach aims to mitigate the catastrophic forgetting phenomenon in a domain incremental setting. The Fisher Information Matrix (FIM) is constructed with EWC to develop a regularization term that penalizes changes to important parameters, namely, the important previous knowledge. CEL's performance is evaluated on three distinct diseases; Influenza, Mpox, and Measles, with different metrics.
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A related paper is submitted to the SCI journal.https://arxiv.org/abs/2401.08940