Identifying Medical Paraphrases in Scientific versus Popularization Texts in F rench for Laypeople Understanding (2022)

Abstract: Scientific medical terms are difficult to understand for laypeople due to their technical formulas and etymology. Understanding medical concepts is important for laypeople as personal and public health is a lifelong concern. In this study, we present our methodology for building a French lexical resource annotated with paraphrases for the simplification of monolexical and multiword medical terms. In order to find medical paraphrases, we automatically searched for medical terms and specific lexical markers that help to paraphrase them. We annotated the medical terms, the paraphrase markers, and the paraphrase. We analysed the lexical relations and semantico-pragmatic functions that exists between the term and its paraphrase. We computed statistics for the medical paraphrase corpus, and we evaluated the readability of the medical paraphrases for a non-specialist coder. Our results show that medical paraphrases from popularization texts are easier to understand (62.66%) than paraphrases extracted from scientific texts (50%).

## introduction understanding medical terms is a challenge for laypeople of all ages and education level. in this study, we concentrated on adults that are not professionals of the medical field but are interested in understanding medical knowledge and research. medical language is difficult to understand due to, partially, the large number of medical terms. the term represents a lexical unit that expresses concepts specific to a field of knowledge, recognised and shared by members of a community of specialists @xcite . the term belongs to an autonomous "subsystem" of the language with the goal of communicating technical or scientific knowledge @xcite . medical terms are particularly difficult to understand because of their greek and/or latin etymology @xcite . they can be composed of a mix of prefixes/suffixes from these two ancient languages together with morphemes of the modern language. laypeople have difficulties in understanding the meaning of medical terms such as "cholecystectomy", which is formed with two greek basis, "chole" (=bile) and "ectomy" (=surgical removal), and in the middle of these, a latin basis, "cystis" (=bladder) @xcite . we can simplify medical terms by using synonyms from the common language, but it is sometimes difficult to find the right synonym. in this paper, we explore the medical paraphrases as means of simplification of medical terms in french. paraphrasing is the process of rewriting in order to explain or simplify a word, sentence, or phrase, while keeping the same meaning. in this paper, we worked on scientific medical texts in french that treat a certain medical concept (diseases, treatments, medical procedures) and on their versions written for laypeople. we looked for paraphrases of these concepts created with simpler words and expressions from the common language. we evaluated the level of difficulty of these medical paraphrases for adult lay readers. the annotated paraphrases will constitute a corpus of medical paraphrases that could be used as a textual resource in natural language processing (nlp) and deep learning tasks. section 2 presents the medical corpus exploited and in section 3 we describe the methodology we used to identify medical terms and paraphrase markers, and thus, the medical paraphrase. we continue with the annotation process in section 4. section 5 describes the evaluation of the medical paraphrases and their readability level according to a non-expert coder whose native language is ## related work in this section, we present several studies on the themes that our research is related to: paraphrases, medical paraphrase corpus, paraphrase markers, medical terms, and automatic paraphrase identification in french. ## methodology for this study, we worked on the clear corpus which is composed of french scientific medical texts and medical texts adapted for laypeople @xcite . our method consisted of automatically identifying simple and multiword medical terms with the sifr-bioportal annotator @xcite . we also tested other annotators for french, such as bio-yodie @xcite and @xcite , but sifr-bioportal proved to be the most intuitive to use. sifr-bioportal works by parsing texts for medical terms from the snomed-3.5vf medical ontology @xcite (released by asip santé). this ontology contains 150,906 scientific medical concepts in french. in order to identify specific markers for the medical domain, we looked for words that collocate with a term and the relations that this term may have with other elements of the sentence. more precisely, we run a perl script to identify relation markers @xcite that link a medical term to its paraphrase @xcite , such as hypernymy, hyponymy, synonymy, meronymy. we expected to find paraphrases in the context of the medical term in the same sentence. after the automatic identification of the medical terms and paraphrase markers, we manually annotated the sentences to find out whether the paraphrases are correct or not. we also annotated the paraphrases for the lexical relations and semantico-pragmatic functions, such as definition, explanations, etc. ## paraphrase annotation process in this section we present different levels of the annotation process of the medical paraphrases. this annotation was manually done in order to assess the quality of the paraphrases that were automatically identified with previous tasks. in this paper we annotated the status of the paraphrase, the lexical relations and the semantico-pragmatic relations that exists between the medical term and its paraphrase. ## results and data evaluation the automatic extraction of the sentences containing both the medical terms annotated by sifr-bioportal and occurrences of markers or paraphrase indicators is done with perl scripts. we adapted our scripts to identify all morphological forms and to automatically annotate medical terms and markers/cues. we obtained 4,681 sentences for the corpus of scientific texts (clear ex) and 3,975 sentences for the corpus of medical texts for the general public (clear gp). these sentences were therefore analysed manually by two coders. we present the results and statistics of these annotations in the tables below. ## conclusion and further research our study has shown that medical paraphrases are present in both scientific and popularization texts. there is a higher number of paraphrases in the general corpus and are also easier to understand, both for annotation tasks and for lay readers comprehension. the analysis and evaluation of lexical relations and semanticopragmatic functions that can be identified between the medical term and its paraphrase highlighted relations such as hyponymy and hyponymy help to identify more correct paraphrases. the same result is observed with the semantico-pragmatic functions of definition and exemplification. in further studies we will also conduct quantitative and qualitative analyses of paraphrase markers (or their absence) and compare them in scientific and popular texts. we could also evaluate the level of readability of each type of lexical relation and semantico-pragmatic function and assess which type of simplifications are easier to understand for laypeople. further analysis could focus on whether the identified paraphrases are scientifically accurate and allow laypeople to be correctly informed about medical topics. here we created a corpus of 1,635 paraphrases of scientific medical terms in french and an annotated corpus of 6,584 phrases that contain scientific medical terms and paraphrase markers. once the annotation process is finished, the annotated corpora will be shared with the scientific community on the github repository. we are currently using the corpus for natural language processing (nlp) tasks such as generating medical paraphrases for scientific our method and experiences can also be applied on other romance languages close to french, such as romanian @xcite . our corpus of medical paraphrases can constitute a useful lexical resource for scientific medical texts simplification system for adult lay readers or patients.