371 citations · 436 across the 10 of their papers we have counts for
11 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…
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…
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…
Correcting Gradient-Based Circuit Localization via Interaction-Aware Backpropagation
Joakim Edin, Casper L. Christensen, Róbert Csordás +5
Circuit localization methods aim to identify the subset of model components responsible for specific behaviors in large language models, enabling detailed mechanistic analysis. Mos…
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…
Self-Supervised Speech Representation Learning: A Review
Abdelrahman Mohamed, Hung-yi Lee, Lasse Borgholt +9
Although supervised deep learning has revolutionized speech and audio processing, it has necessitated the building of specialist models for individual tasks and application scenari…
A Brief Overview of Unsupervised Neural Speech Representation Learning
Lasse Borgholt, Jakob Drachmann Havtorn, Joakim Edin +2
Unsupervised representation learning for speech processing has matured greatly in the last few years. Work in computer vision and natural language processing has paved the way, but…
Do We Still Need Automatic Speech Recognition for Spoken Language Understanding?
Lasse Borgholt, Jakob Drachmann Havtorn, Mostafa Abdou +4
Spoken language understanding (SLU) tasks are usually solved by first transcribing an utterance with automatic speech recognition (ASR) and then feeding the output to a text-based…
MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech
Jakob D. Havtorn, Jan Latko, Joakim Edin +6
We address a challenging and practical task of labeling questions in speech in real time during telephone calls to emergency medical services in English, which embeds within a broa…