Large Language models (LLMs) are rapidly being adopted for tasks such as text
summarization, in a wide range of industries. This has driven the need for scalable …

Medical decisions directly impact individuals' health and well-being. Extracting decision
spans from clinical notes plays a crucial role in understanding medical decision-making …

Clinical coding is crucial for healthcare billing and data analysis. Manual clinical coding is
labour-intensive and error-prone, which has motivated research towards full automation of …

Electronic healthcare records are vital for patient safety as they document conditions, plans,
and procedures in both free text and medical codes. Language models have significantly …

To address the limitations of Large Language Models (LLMs) in the International
Classification of Diseases (ICD) coding task, where they often produce inaccurate and …

Electronic Health Records (EHR) serve as a valuable source of patient information, offering
insights into medical histories, treatments, and outcomes. Previous research has developed …

Data annotations in datasets used for machine learning are often produced by human
annotation or other noisy processes. Systematic label errors may be introduced to datasets …

Clinical coding involves the classification of medical diagnoses and procedures using
alphanumeric codes. Manual coding is labourintensive and error-prone, motivating research …