Joakim Edin — accepted AI-conference papers

2025

Code Like Humans: A Multi-Agent Solution for Medical Coding

Andreas Geert Motzfeldt, Joakim Edin, Casper L. Christensen, Christian Hardmeier, Lars Maal{\o}e, Anna Rogers

EMNLP 2025

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 coding with large language models. It implements official coding guidelines for human experts, and it is the first solut

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2025

Normalized AOPC: Fixing Misleading Faithfulness Metrics for Feature Attributions Explainability

Joakim Edin, Andreas Geert Motzfeldt, Casper L. Christensen, Tuukka Ruotsalo, Lars Maaløe, Maria Maistro

ACL 2025long

Deep neural network predictions are notoriously difficult to interpret. Feature attribution methods aim to explain these predictions by identifying the contribution of each input feature. Faithfulness, often evaluated using the area over the perturbation curve (AOPC), reflects feature attributions’…

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2024

An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records

Joakim Edin, Maria Maistro, Lars Maaløe, Lasse Borgholt, Jakob Drachmann Havtorn, Tuukka Ruotsalo

EMNLP 2024main

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 enhanced the processing of such records, streamlining workflows and reducing manual data entry, thereby saving healthc…

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