% This must be in the first 5 lines to tell arXiv to use pdfLaTeX, which is strongly recommended.
\pdfoutput=1
% In particular, the hyperref package requires pdfLaTeX in order to break URLs across lines.

\documentclass[11pt]{article}

% Change "review" to "final" to generate the final (sometimes called camera-ready) version.
% Change to "preprint" to generate a non-anonymous version with page numbers.
% \usepackage[review]{acl}
\usepackage[final]{acl}

\usepackage{hyperref}

% Standard package includes
\usepackage{times}
\usepackage{latexsym}

% For proper rendering and hyphenation of words containing Latin characters (including in bib files)
\usepackage[T1]{fontenc}
% For Vietnamese characters
% \usepackage[T5]{fontenc}
% See https://www.latex-project.org/help/documentation/encguide.pdf for other character sets

% This assumes your files are encoded as UTF8
\usepackage[utf8]{inputenc}

% This is not strictly necessary, and may be commented out,
% but it will improve the layout of the manuscript,
% and will typically save some space.
\usepackage{microtype}

\usepackage{svg}
% This is also not strictly necessary, and may be commented out.
% However, it will improve the aesthetics of text in
% the typewriter font.
\usepackage{inconsolata}

%Including images in your LaTeX document requires adding
%additional package(s)
\usepackage{graphicx}
\usepackage{hyperref}
\usepackage{booktabs}
\usepackage{multirow}
\usepackage{array}
\usepackage{amsmath}
% If the title and author information does not fit in the area allocated, uncomment the following
%
%\setlength\titlebox{<dim>}
%
% and set <dim> to something 5cm or larger.
\usepackage{scalerel,xparse}
\newcommand{\emojien}{\scalerel*{\includegraphics{images/flag-en.png}}{X}}

\title{A Retrieval-Based Approach to Medical Procedure Matching in Romanian}
% matching de denumiri, medical, real-world, Romanian

\author{Andrei Niculae\textsuperscript{1}, Adrian Cosma\textsuperscript{1,2}, Emilian Radoi\textsuperscript{1} \\
  \textsuperscript{1}National University of Science and Technology POLITEHNICA Bucharest \\
  \textsuperscript{2}Dalle Molle Institute for Artificial Intelligence Research (IDSIA) \\
  \texttt{\normalsize andrei.niculae1004@stud.acs.upb.ro, adrian.cosma@supsi.ch, emilian.radoi@upb.ro} \\
}

\begin{document}
\maketitle
\begin{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.
\end{abstract}

\section{Introduction}
\input{sections/1.intro}

\section{Related Work}
\input{sections/2.related}

\section{Method}
\input{sections/3.method}

\section{Experiments and Results}\label{results}
\input{sections/4.experiments-results}

\section{Conclusion}
\input{sections/5.conclusions}

\section*{Limitations}
\input{sections/6.limitations}

\section*{Acknowledgement}
\input{sections/7.acknowledgement}

% Entries for the entire Anthology, followed by custom entries
\bibliography{refs}

\end{document}
