Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks.

ABSTRACT: Standard reference terminology of diagnoses and risk factors is crucial for billing, epidemiological studies, and inter/intranational comparisons of diseases. The International Classification of Disease (ICD) is a standardized and widely used method, but the manual classification is an enormously time-consuming endeavor. Natural language processing together with machine learning allows automated structuring of diagnoses using ICD-10 codes, but the limited performance of machine learning models, the necessity of gigantic datasets, and poor reliability of terminal parts of these codes restricted clinical usability. We aimed to create a high performing pipeline for automated classification of reliable ICD-10 codes in the free medical text in cardiology. We focussed on frequently used and well

SUBMITTER: Sammani A 

PROVIDER: S-EPMC7910461 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature