86 citations · 90 across the 6 of their papers we have counts for
6 papers
Symphony for Medical Coding: A Next-Generation Agentic System for Scalable and Explainable Medical Coding
Joakim Edin, Andreas Motzfeldt, Simon Flachs +1
Medical coding translates free-text clinical documentation into standardized codes drawn from classification systems that contain tens of thousands of entries and are updated annua…
Code Like Humans: A Multi-Agent Solution for Medical Coding
Andreas Motzfeldt, Joakim Edin, Casper L. Christensen +3
In medical coding, experts map unstructured clinical notes to alphanumeric codes for diagnoses and procedures. We introduce Code Like Humans: a new agentic framework for medical co…
FactsR: A Safer Method for Producing High Quality Healthcare Documentation
Victor Petrén Bach Hansen, Lasse Krogsbøll, Jonas Lyngsø +4
There are now a multitude of AI-scribing solutions for healthcare promising the utilization of large language models for ambient documentation. However, these AI scribes still rely…
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…
Variational Open-Domain Question Answering
Valentin Liévin, Andreas Geert Motzfeldt, Ida Riis Jensen +1
Retrieval-augmented models have proven to be effective in natural language processing tasks, yet there remains a lack of research on their optimization using variational inference.…
Can large language models reason about medical questions?
Valentin Liévin, Christoffer Egeberg Hother, Andreas Geert Motzfeldt +1
Although large language models (LLMs) often produce impressive outputs, it remains unclear how they perform in real-world scenarios requiring strong reasoning skills and expert dom…