Multitask Balanced and Recalibrated Network for Medical Code Prediction

Understand

Human coders assign standardized medical codes to clinical documents generated during patients' hospitalization, which is error-prone and labor-intensive.

• Automated medical coding approaches have been developed using machine learning methods such as deep neural networks.
• Nevertheless, automated medical coding is still challenging because of the imbalanced class problem, complex code association, and noise in lengthy documents.
• To solve these issues, we propose a novel neural network called Multitask Balanced and Recalibrated Neural Network.