![]() ![]() Coders are needed to be involved in the development process. Automated clinical coding is a promising task for AI, despite the technical and organisational challenges. Knowledge-based methods that represent and reason the standard, explainable process of a task may need to be incorporated into deep learning-based methods for clinical coding. Our research reveals the gaps between the current deep learning-based approach applied to clinical coding and the need for explainability and consistency in real-world practice. ![]() We introduce the idea of automated clinical coding and summarise its challenges from the perspective of Artificial Intelligence (AI) and Natural Language Processing (NLP), based on the literature, our project experience over the past two and half years (late 2019–early 2022), and discussions with clinical coding experts in Scotland and the UK. Clinical coding could potentially be supported by an automated system to improve the efficiency and accuracy of the process. This is a cognitive and time-consuming task that follows a standard process in order to achieve a high level of consistency. ![]() Clinical coding is the task of transforming medical information in a patient’s health records into structured codes so that they can be used for statistical analysis. ![]()
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