The automated coding task aims to match medical text records with the corresponding International Classification of Diseases (ICD) codes to improve the efficiency and accuracy of medical record management. In the automatic coding task, existing methods often face the challenge of label bias, a problem that affects the overall performance of the model. To address this challenge, we propose a new bias removal method that aims to optimize model performance. Furthermore, we note that some samples are difficult to be recognized during the encoding process due to their complexity. Given the huge amo...
