| Vol-3985 urn:nbn:de:0074-3985-X Copyright © 2025 for the individual papers by the papers' authors. Copyright © 2025 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# SLM4Health 2025
Improving Healthcare with Small Language Models

### Proceedings of the First International Workshop on Improving Healthcare with Small Language Models, SLM4Health 2025
co-located with 23rd International Conference on Artificial Intelligence in Medicine (AIME 2025)

### Pavia, Italy, June 26, 2025.

Edited by

### Kerstin Denecke 1
Douglas Teodoro 2
Daniel Reichenpfader 1,2
Yihan Deng 1,2
Edward Choi 3

1 Bern University of Applied Sciences, School of Engineering and Computer Science, 2501 Biel, Switzerland
2 University of Geneva, Department of Radiology and Medical Informatics, Faculty of Medicine, 1211 Geneva, Switzerland
3 Korea Advanced Institute of Science and Technology, Graduate School of AI, College of Engineering, 34141 Daejeon, Republic of Korea

## Table of Contents

- Preface
  Summary: There were 6 papers submitted for peer-review to this workshop; 6 papers were accepted for this volume; 6 are regular papers.

### Session 1: From Detection to Diagnosis: Small Language Models in Medical and Assistive AI

- A Health-Focused Risk Taxonomy for AI: Assessing Unsafe Content Detection with Small Language Models (SLMs) 1-9
  Lantana Hewitt, Abdel-Karim Al Tamimi, Robert Copeland, Richard Moore, Shaman Jhanji
- Enhancing Aphasia Speech Interpretation using Small Language Models (SLMs) 10-18
  Abdel-Karim Al-Tamimi, Kate Radford, Jacqueline Benfield, Jacob Andrews, Catherine Sweby
- Exploring the Role of Knowledge Graph-Based RAG in Japanese Medical Question Answering with Small-Scale LLMs 19-28
  Yingjian Chen, Feiyang Li, Xingyu Song, Tianxiao Li, Zixin Xu, Xiujie Chen, Issey Sukeda, Irene Li

### Session 2: SLM for Clinical NLP – Power and Limitations

- Exploring the Missing Medical Context in Generated Radiology Reports 25-32
  Karan Bania, Harshvardhan Mestha, Tanmay Verlekar
- Embedding-Based Acronym Disambiguation Supported by Large Language Models in German Clinical Narratives 33-40
  Amila Kugic, Stefan Schulz, Markus Kreuzthaler
- Large language models versus static word embeddings to predict Acute Kidney Injury in the Intensive Care Unit: Does context matter? 41-50
  Rick van Slobbe, Drahomira Herrmannova, Elia S Lima-Walton, Ameen Abu-Hanna, Iacopo Vagliano

2025-06-17: submitted by Kerstin Denecke, metadata incl. bibliographic data published under Creative Commons CC0
2025-06-26: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|