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    <titleInfo>
        <title>A Retrieval-Based Approach to Medical Procedure Matching in Romanian</title>
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    <name type="personal">
        <namePart type="given">Andrei</namePart>
        <namePart type="family">Niculae</namePart>
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    <name type="personal">
        <namePart type="given">Adrian</namePart>
        <namePart type="family">Cosma</namePart>
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    <name type="personal">
        <namePart type="given">Emilian</namePart>
        <namePart type="family">Radoi</namePart>
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            <title>Proceedings of the 24th Workshop on Biomedical Language Processing</title>
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        <name type="personal">
            <namePart type="given">Dina</namePart>
            <namePart type="family">Demner-Fushman</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Sophia</namePart>
            <namePart type="family">Ananiadou</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Makoto</namePart>
            <namePart type="family">Miwa</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Junichi</namePart>
            <namePart type="family">Tsujii</namePart>
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    <abstract>Accurately mapping medical procedure names from healthcare providers to standardized terminology used by insurance companies is a crucial yet complex task. Inconsistencies in naming conventions lead to missclasified procedures, causing administrative inefficiencies and insurance claim problems in private healthcare settings. Many companies still use human resources for manual mapping, while there is a clear opportunity for automation. This paper proposes a retrieval-based architecture leveraging sentence embeddings for medical name matching in the Romanian healthcare system. This challenge is significantly more difficult in underrepresented languages such as Romanian, where existing pretrained language models lack domain-specific adaptation to medical text. We evaluate multiple embedding models, including Romanian, multilingual, and medical-domain-specific representations, to identify the most effective solution for this task. Our findings contribute to the broader field of medical NLP for low-resource languages such as Romanian.</abstract>
    <identifier type="citekey">niculae-etal-2025-retrieval</identifier>
    <identifier type="doi">10.18653/v1/2025.bionlp-1.15</identifier>
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        <date>2025-08</date>
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            <start>167</start>
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%0 Conference Proceedings
%T A Retrieval-Based Approach to Medical Procedure Matching in Romanian
%A Niculae, Andrei
%A Cosma, Adrian
%A Radoi, Emilian
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Miwa, Makoto
%Y Tsujii, Junichi
%S Proceedings of the 24th Workshop on Biomedical Language Processing
%D 2025
%8 August
%I Association for Computational Linguistics
%C Viena, Austria
%@ 979-8-89176-275-6
%F niculae-etal-2025-retrieval
%X Accurately mapping medical procedure names from healthcare providers to standardized terminology used by insurance companies is a crucial yet complex task. Inconsistencies in naming conventions lead to missclasified procedures, causing administrative inefficiencies and insurance claim problems in private healthcare settings. Many companies still use human resources for manual mapping, while there is a clear opportunity for automation. This paper proposes a retrieval-based architecture leveraging sentence embeddings for medical name matching in the Romanian healthcare system. This challenge is significantly more difficult in underrepresented languages such as Romanian, where existing pretrained language models lack domain-specific adaptation to medical text. We evaluate multiple embedding models, including Romanian, multilingual, and medical-domain-specific representations, to identify the most effective solution for this task. Our findings contribute to the broader field of medical NLP for low-resource languages such as Romanian.
%R 10.18653/v1/2025.bionlp-1.15
%U https://aclanthology.org/2025.bionlp-1.15/
%U https://doi.org/10.18653/v1/2025.bionlp-1.15
%P 167-175

Markdown (Informal)

[A Retrieval-Based Approach to Medical Procedure Matching in Romanian](https://aclanthology.org/2025.bionlp-1.15/) (Niculae et al., BioNLP 2025)

• A Retrieval-Based Approach to Medical Procedure Matching in Romanian (Niculae et al., BioNLP 2025)

ACL

• Andrei Niculae, Adrian Cosma, and Emilian Radoi. 2025. A Retrieval-Based Approach to Medical Procedure Matching in Romanian. In Proceedings of the 24th Workshop on Biomedical Language Processing, pages 167–175, Viena, Austria. Association for Computational Linguistics.