Do pelvic floor muscle function parameters differ in women according to continence status? A systematic review.

Background: Current literature highlights the difficulty in identifying which pelvic floor muscle (PFM) functions are correlated with urinary incontinence (UI).

Aim: In this study, we compared parameters of PFM function (strength, endurance, tone, control, reaction, and/or coordination) according to continence status in women (presence or absence, type and/or severity of urinary incontinence).

Evidence Acquisition: A systematic review was conducted following the 2020 PRISMA guidelines.

Designing Formulae for Ranking Search Results: Mixed Methods Evaluation Study.

Background: A major factor in the success of any search engine is the relevance of the search results; a tool should sort the search results to present the most relevant documents first. Assessing the performance of the ranking formula is an important part of search engine evaluation. However, the methods currently used to evaluate ranking formulae mainly collect quantitative data and do not gather qualitative data, which help to understand what needs to be improved to tailor the formulae to their end users.

Identification of the Best Semantic Expansion to Query PubMed Through Automatic Performance Assessment of Four Search Strategies on All Medical Subject Heading Descriptors: Comparative Study.

Background: With the continuous expansion of available biomedical data, efficient and effective information retrieval has become of utmost importance. Semantic expansion of queries using synonyms may improve information retrieval.

Objective: The aim of this study was to automatically construct and evaluate expanded PubMed queries of the form "preferred term"[MH] OR "preferred term"[TIAB] OR "synonym 1"[TIAB] OR "synonym 2"[TIAB] OR …, for each of the 28,313 Medical Subject Heading (MeSH) descriptors, by using different semantic expansion strategies.

Performance evaluation of three semantic expansions to query PubMed.

Background: PubMed is one of the most important basic tools to access medical literature. Semantic query expansion using synonyms can improve retrieval efficacy.

Objective: The objective was to evaluate the performance of three semantic query expansion strategies.

Word Embedding for French Natural Language in Healthcare: A Comparative Study.

Structuring raw medical documents with ontology mapping is now the next step for medical intelligence. Deep learning models take as input mathematically embedded information, such as encoded texts. To do so, word embedding methods can represent every word from a text as a fixed-length vector.

Word Embedding for the French Natural Language in Health Care: Comparative Study.

Background: Word embedding technologies, a set of language modeling and feature learning techniques in natural language processing (NLP), are now used in a wide range of applications. However, no formal evaluation and comparison have been made on the ability of each of the 3 current most famous unsupervised implementations (Word2Vec, GloVe, and FastText) to keep track of the semantic similarities existing between words, when trained on the same dataset.

Objective: The aim of this study was to compare embedding methods trained on a corpus of French health-related documents produced in a professional context.

Lost in translation? A multilingual Query Builder improves the quality of PubMed queries: a randomised controlled trial.

Background: MEDLINE is the most widely used medical bibliographic database in the world. Most of its citations are in English and this can be an obstacle for some researchers to access the information the database contains. We created a multilingual query builder to facilitate access to the PubMed subset using a language other than English.

Behavior and attitudes of residents and general practitioners in searching for health information: From intention to practice.

Background: Physicians are increasingly encouraged to practice evidence-based medicine (EBM), and their decisions require evidence based on valid research. Existing literature shows a mismatch between general practitioners' (GPs) information needs and evidence available online. The aim of this study was to explore the attitudes and behavior of residents in general medicine and GPs when seeking medical information online.

Evaluation of Internet Social Networks using Net scoring Tool: A Case Study in Adverse Drug Reaction Mining.

Background And Objectives: Suspected adverse drug reactions (ADR) reported by patients through social media can be a complementary tool to already existing ADRs signal detection processes. However, several studies have shown that the quality of medical information published online varies drastically whatever the health topic addressed. The aim of this study is to use an existing rating tool on a set of social network web sites in order to assess the capabilities of these tools to guide experts for selecting the most adapted social network web site to mine ADRs.

A search engine to access PubMed monolingual subsets: proof of concept and evaluation in French.

Background: PubMed contains numerous articles in languages other than English. However, existing solutions to access these articles in the language in which they were written remain unconvincing.

Objective: The aim of this study was to propose a practical search engine, called Multilingual PubMed, which will permit access to a PubMed subset in 1 language and to evaluate the precision and coverage for the French version (Multilingual PubMed-French).

Design and usability study of an iconic user interface to ease information retrieval of medical guidelines.

Background And Objective: Doc'CISMeF (DC) is a semantic search engine used to find resources in CISMeF-BP, a quality controlled health gateway, which gathers guidelines available on the internet in French. Visualization of Concepts in Medicine (VCM) is an iconic language that may ease information retrieval tasks. This study aimed to describe the creation and evaluation of an interface integrating VCM in DC in order to make this search engine much easier to use.

Evaluating alignment quality between iconic language and reference terminologies using similarity metrics.

Background: Visualization of Concepts in Medicine (VCM) is a compositional iconic language that aims to ease information retrieval in Electronic Health Records (EHR), clinical guidelines or other medical documents. Using VCM language in medical applications requires alignment with medical reference terminologies. Alignment from Medical Subject Headings (MeSH) thesaurus and International Classification of Diseases - tenth revision (ICD10) to VCM are presented here.

Multi-lingual search engine to access PubMed monolingual subsets: a feasibility study.

PubMed contains many articles in languages other than English but it is difficult to find them using the English version of the Medical Subject Headings (MeSH) Thesaurus. The aim of this work is to propose a tool allowing access to a PubMed subset in one language, and to evaluate its performance. Translations of MeSH were enriched and gathered in the information system.

Validating the semantics of a medical iconic language using ontological reasoning.

To help clinicians read medical texts such as clinical practice guidelines or drug monographs, we proposed an iconic language called VCM. This language can use icons to represent the main medical concepts, including diseases, symptoms, treatments and follow-up procedures, by combining various pictograms, shapes and colors. However, the semantics of this language have not been formalized, and users may create inconsistent icons, e.

Performance evaluation of Unified Medical Language System®'s synonyms expansion to query PubMed.

Background: PubMed is the main access to medical literature on the Internet. In order to enhance the performance of its information retrieval tools, primarily non-indexed citations, the authors propose a method: expanding users' queries using Unified Medical Language System' (UMLS) synonyms i.e.

Towards iconic language for patient records, drug monographs, guidelines and medical search engines.

Practicing physicians have limited time for consulting medical knowledge and records. We have previously shown that using icons instead of text to present drug monographs may allow contraindications and adverse effects to be identified more rapidly and more accurately. These findings were based on the use of an iconic language designed for drug knowledge, providing icons for many medical concepts, including diseases, antecedents, drug classes and tests.

Relevance of Google-customized search engine vs. CISMeF quality-controlled health gateway.

CISMeF (acronym for Catalog and Index of French Language Health Resources on the Internet) is a quality-controlled health gateway conceived to catalog and index the most important and quality-controlled sources of institutional health information in French. The goal of this study is to compare the relevance of results provided by this gateway from a small set of documents selected and described by human experts to those provided by a search engine from a large set of automatically indexed and ranked resources. The Google-Customized search engine (CSE) was used.

Multi-terminology indexing for the assignment of MeSH descriptors to medical abstracts in French.

Background: To facilitate information retrieval in the biomedical domain, a system for the automatic assignment of Medical Subject Headings to documents curated by an online quality-controlled health gateway was implemented. The French Multi-Terminology Indexer (F-MTI) implements a multiterminology approach using nine main medical terminologies in French and the mappings between them.

Objective: This paper presents recent efforts to assess the added value of (a) integrating four new terminologies (Orphanet, ATC, drug names, MeSH supplementary concepts) into F-MTI's knowledge sources and (b) performing the automatic indexing on the titles and abstracts (vs.

Using multi-terminology indexing for the assignment of MeSH descriptors to health resources in a French online catalogue.

Background: To assist with the development of a French online quality-controlled health gateway(CISMeF), an automatic indexing tool assigning MeSH descriptors to medical text in French was created. The French Multi-Terminology Indexer (FMTI) relies on a multi-terminology approach involving four prominent medical terminologies and the mappings between them.

Objective: In this paper,we compare lemmatization and stemming as methods to process French medical text for indexing.

Evaluation of a simple method for the automatic assignment of MeSH descriptors to health resources in a French online catalogue.

Background: The growing number of resources to be indexed in the catalogue of online health resources in French (CISMeF) calls for curating strategies involving automatic indexing tools while maintaining the catalogue's high indexing quality standards.

Objective: To develop a simple automatic tool that retrieves MeSH descriptors from documents titles.

Methods: In parallel to research on advanced indexing methods, a bag-of-words tool was developed for timely inclusion in CISMeF's maintenance system.