An Intelligent System for Healthcare Service Logging in a Medium-Sized Language

We present an intelligent system designed for the environment of a healthcare facility, such as a hospital or a nursing home. The aim of the system is to log the services carried out by the service provider (a nurse) without the need to choose individual items from a series of menus, which is currently the standard procedure. Instead, we used a voice recording of the nurses reporting their actions in a natural language, i.e. without particular voice commands, coupled with a fine-tuned Large Language Model (LLM). We discuss legal aspects related to recording and processing of conversations in a healthcare facility. We outline the implementation and present the results of tests using different types of LLMs. We focus on the Slovenian language, which can be seen as a medium-sized language, instead of English which is widely supported by LLMs. Our approach produces up to 97% both in precision and recall.

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Published
2025-06-23
DOI
https://doi.org/10.1109/ie64880.2025.11130115
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

An Intelligent System for Healthcare Service Logging in a Medium-Sized Language

Robert Susič, Anton Gradišek, Maj Smerkol, Gizem Gültekin Várkonyi et al.
Artificial Intelligence in Healthcare
article

An Intelligent System for Healthcare Service Logging in a Medium-Sized Language

Robert Susič, Anton Gradišek, Maj Smerkol, Gizem Gültekin Várkonyi, Tomo Jarc
article en

Abstract

We present an intelligent system designed for the environment of a healthcare facility, such as a hospital or a nursing home. The aim of the system is to log the services carried out by the service provider (a nurse) without the need to choose individual items from a series of menus, which is currently the standard procedure. Instead, we used a voice recording of the nurses reporting their actions in a natural language, i.e. without particular voice commands, coupled with a fine-tuned Large Language Model (LLM). We discuss legal aspects related to recording and processing of conversations in a healthcare facility. We outline the implementation and present the results of tests using different types of LLMs. We focus on the Slovenian language, which can be seen as a medium-sized language, instead of English which is widely supported by LLMs. Our approach produces up to 97% both in precision and recall.

University of Ljubljana (SI), University of Szeged (HU), Jožef Stefan Institute (SI), Kranj School Centre (SI)
Openalex Percentile: Top 75%
Artificial Intelligence in Healthcare
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