371 citations · 436 across the 10 of their papers we have counts for
4 papers · 1 filter
A medical coding language model trained on clinical narratives from a population-wide cohort of 1.8 million patients
Joakim Edin, Sedrah Butt Balaganeshan, Annike Kjølby Kristensen +3
Medical coding translates clinical documentation into standardized codes for billing, research, and public health, but manual coding is time-consuming and error-prone. Existing aut…
Normalized AOPC: Fixing Misleading Faithfulness Metrics for Feature Attribution Explainability
Joakim Edin, Andreas Geert Motzfeldt, Casper L. Christensen +3
Deep neural network predictions are notoriously difficult to interpret. Feature attribution methods aim to explain these predictions by identifying the contribution of each input f…
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records
Joakim Edin, Maria Maistro, Lars Maaløe +3
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 significantl…
Automated Medical Coding on MIMIC-III and MIMIC-IV: A Critical Review and Replicability Study
Joakim Edin, Alexander Junge, Jakob D. Havtorn +4
Medical coding is the task of assigning medical codes to clinical free-text documentation. Healthcare professionals manually assign such codes to track patient diagnoses and treatm…