Multitask Recalibrated Aggregation Network for Medical Code Prediction
Published in ECML 2021, 2021
Recommended citation: Sun, Wei, et al. "Multitask Recalibrated Aggregation Network for Medical Code Prediction." arXiv preprint arXiv:2104.00952 (2021). https://link.springer.com/chapter/10.1007/978-3-030-86514-6_23
We proposed a novel multitask framework (MT-RAM) for the automated medical coding task, which improved feature learning for clinical documents and accounted for the dependencies between different medical coding systems (ICD coding & CCS coding). We designed a Recalibrated Aggregation Module (RAM) to enrich document features and reduce noisy information. Furthermore, we leveraged multitask learning to share information across different medical codes.
Recommended citation: Sun, Wei, et al. “Multitask Recalibrated Aggregation Network for Medical Code Prediction.” arXiv preprint arXiv:2104.00952 (2021).