Journal of Biomedical Semantics最新文献

{"title":"Pathling: analytics on FHIR.","authors":"John Grimes,&nbsp;Piotr Szul,&nbsp;Alejandro Metke-Jimenez,&nbsp;Michael Lawley,&nbsp;Kylynn Loi","doi":"10.1186/s13326-022-00277-1","DOIUrl":"https://doi.org/10.1186/s13326-022-00277-1","url":null,"abstract":"<p><strong>Background: </strong>Health data analytics is an area that is facing rapid change due to the acceleration of digitization of the health sector, and the changing landscape of health data and clinical terminology standards. Our research has identified a need for improved tooling to support analytics users in the task of analyzing Fast Healthcare Interoperability Resources (FHIR^®) data and associated clinical terminology.</p><p><strong>Results: </strong>A server implementation was developed, featuring a FHIR API with new operations designed to support exploratory data analysis (EDA), advanced patient cohort selection and data preparation tasks. Integration with a FHIR Terminology Service is also supported, allowing users to incorporate knowledge from rich terminologies such as SNOMED CT within their queries. A prototype user interface for EDA was developed, along with visualizations in support of a health data analysis project.</p><p><strong>Conclusions: </strong>Experience with applying this technology within research projects and towards the development of analytics-enabled applications provides a preliminary indication that the FHIR Analytics API pattern implemented by Pathling is a valuable abstraction for data scientists and software developers within the health care domain. Pathling contributes towards the value proposition for the use of FHIR within health data analytics, and assists with the use of complex clinical terminologies in that context.</p>","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":"13 1","pages":"23"},"PeriodicalIF":1.9,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9455941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10470739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Figuring Out Root and Epistemic Uses of Modals: The Role of the Input","authors":"Annemarie van Dooren, Anouk Dieuleveut, Ailís Cournane, V. Hacquard","doi":"10.1093/jos/ffac010","DOIUrl":"https://doi.org/10.1093/jos/ffac010","url":null,"abstract":"\u0000 This paper investigates how children figure out that modals like must can be used to express both epistemic and “root” (i.e. non epistemic) flavors. The existing acquisition literature shows that children produce modals with epistemic meanings up to a year later than with root meanings. We conducted a corpus study to examine how modality is expressed in speech to and by young children, to investigate the ways in which the linguistic input children hear may help or hinder them in uncovering the flavor flexibility of modals. Our results show that the way parents use modals may obscure the fact that they can express epistemic flavors: modals are very rarely used epistemically. Yet, children eventually figure it out; our results suggest that some do so even before age 3. To investigate how children pick up on epistemic flavors, we explore distributional cues that distinguish roots and epistemics. The semantic literature argues they differ in “temporal orientation” (Condoravdi, 2002): while epistemics can have present or past orientation, root modals tend to be constrained to future orientation (Werner 2006; Klecha, 2016; Rullmann & Matthewson, 2018). We show that in child-directed speech, this constraint is well-reflected in the distribution of aspectual features of roots and epistemics, but that the signal might be weak given the strong usage bias towards roots. We discuss (a) what these results imply for how children might acquire adult-like modal representations, and (b) possible learning paths towards adult-like modal representations.","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":"81 1","pages":"581-616"},"PeriodicalIF":1.9,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79294875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of missing hierarchical relations in the vaccine ontology using acquired term pairs.","authors":"Warren Manuel,&nbsp;Rashmie Abeysinghe,&nbsp;Yongqun He,&nbsp;Cui Tao,&nbsp;Licong Cui","doi":"10.1186/s13326-022-00276-2","DOIUrl":"https://doi.org/10.1186/s13326-022-00276-2","url":null,"abstract":"<p><strong>Background: </strong>The Vaccine Ontology (VO) is a biomedical ontology that standardizes vaccine annotation. Errors in VO will affect a multitude of applications that it is being used in. Quality assurance of VO is imperative to ensure that it provides accurate domain knowledge to these downstream tasks. Manual review to identify and fix quality issues (such as missing hierarchical is-a relations) is challenging given the complexity of the ontology. Automated approaches are highly desirable to facilitate the quality assurance of VO.</p><p><strong>Methods: </strong>We developed an automated lexical approach that identifies potentially missing is-a relations in VO. First, we construct two types of VO concept-pairs: (1) linked; and (2) unlinked. Each concept-pair further derives an Acquired Term Pair (ATP) based on their lexical features. If the same ATP is obtained by a linked concept-pair and an unlinked concept-pair, this is considered to indicate a potentially missing is-a relation between the unlinked pair of concepts.</p><p><strong>Results: </strong>Applying this approach on the 1.1.192 version of VO, we were able to identify 232 potentially missing is-a relations. A manual review by a VO domain expert on a random sample of 70 potentially missing is-a relations revealed that 65 of the cases were valid missing is-a relations in VO (a precision of 92.86%).</p><p><strong>Conclusions: </strong>The results indicate that our approach is highly effective in identifying missing is-a relation in VO.</p>","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":" ","pages":"22"},"PeriodicalIF":1.9,"publicationDate":"2022-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9375092/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40611283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DCSO: towards an ontology for machine-actionable data management plans.","authors":"João Cardoso,&nbsp;Leyla J Castro,&nbsp;Fajar J Ekaputra,&nbsp;Marie C Jacquemot,&nbsp;Marek Suchánek,&nbsp;Tomasz Miksa,&nbsp;José Borbinha","doi":"10.1186/s13326-022-00274-4","DOIUrl":"https://doi.org/10.1186/s13326-022-00274-4","url":null,"abstract":"<p><p>The concept of Data Management Plan (DMP) has emerged as a fundamental tool to help researchers through the systematical management of data. The Research Data Alliance DMP Common Standard (DCS) working group developed a set of universal concepts characterising a DMP so it can be represented as a machine-actionable artefact, i.e., machine-actionable Data Management Plan (maDMP). The technology-agnostic approach of the current maDMP specification: (i) does not explicitly link to related data models or ontologies, (ii) has no standardised way to describe controlled vocabularies, and (iii) is extensible but has no clear mechanism to distinguish between the core specification and its extensions.This paper reports on a community effort to create the DMP Common Standard Ontology (DCSO) as a serialisation of the DCS core concepts, with a particular focus on a detailed description of the components of the ontology. Our initial result shows that the proposed DCSO can become a suitable candidate for a reference serialisation of the DMP Common Standard.</p>","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":" ","pages":"21"},"PeriodicalIF":1.9,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9327208/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40625989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: PhenoDEF: a corpus for annotating sentences with information of phenotype definitions in biomedical literature.","authors":"Samar Binkheder,&nbsp;Heng-Yi Wu,&nbsp;Sara K Quinney,&nbsp;Shijun Zhang,&nbsp;Md Muntasir Zitu,&nbsp;Chien-Wei Chiang,&nbsp;Lei Wang,&nbsp;Josette Jones,&nbsp;Lang Li","doi":"10.1186/s13326-022-00275-3","DOIUrl":"https://doi.org/10.1186/s13326-022-00275-3","url":null,"abstract":"","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":" ","pages":"20"},"PeriodicalIF":1.9,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40539574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance assessment of ontology matching systems for FAIR data.","authors":"Philip van Damme,&nbsp;Jesualdo Tomás Fernández-Breis,&nbsp;Nirupama Benis,&nbsp;Jose Antonio Miñarro-Gimenez,&nbsp;Nicolette F de Keizer,&nbsp;Ronald Cornet","doi":"10.1186/s13326-022-00273-5","DOIUrl":"https://doi.org/10.1186/s13326-022-00273-5","url":null,"abstract":"<p><strong>Background: </strong>Ontology matching should contribute to the interoperability aspect of FAIR data (Findable, Accessible, Interoperable, and Reusable). Multiple data sources can use different ontologies for annotating their data and, thus, creating the need for dynamic ontology matching services. In this experimental study, we assessed the performance of ontology matching systems in the context of a real-life application from the rare disease domain. Additionally, we present a method for analyzing top-level classes to improve precision.</p><p><strong>Results: </strong>We included three ontologies (NCIt, SNOMED CT, ORDO) and three matching systems (AgreementMakerLight 2.0, FCA-Map, LogMap 2.0). We evaluated the performance of the matching systems against reference alignments from BioPortal and the Unified Medical Language System Metathesaurus (UMLS). Then, we analyzed the top-level ancestors of matched classes, to detect incorrect mappings without consulting a reference alignment. To detect such incorrect mappings, we manually matched semantically equivalent top-level classes of ontology pairs. AgreementMakerLight 2.0, FCA-Map, and LogMap 2.0 had F1-scores of 0.55, 0.46, 0.55 for BioPortal and 0.66, 0.53, 0.58 for the UMLS respectively. Using vote-based consensus alignments increased performance across the board. Evaluation with manually created top-level hierarchy mappings revealed that on average 90% of the mappings' classes belonged to top-level classes that matched.</p><p><strong>Conclusions: </strong>Our findings show that the included ontology matching systems automatically produced mappings that were modestly accurate according to our evaluation. The hierarchical analysis of mappings seems promising when no reference alignments are available. All in all, the systems show potential to be implemented as part of an ontology matching service for querying FAIR data. Future research should focus on developing methods for the evaluation of mappings used in such mapping services, leading to their implementation in a FAIR data ecosystem.</p>","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":" ","pages":"19"},"PeriodicalIF":1.9,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284868/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40597376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploiting document graphs for inter sentence relation extraction","authors":"Hoang-Quynh Le, Duy-Cat Can, Nigel Collier","doi":"10.1186/s13326-022-00267-3","DOIUrl":"https://doi.org/10.1186/s13326-022-00267-3","url":null,"abstract":"","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":"13 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2022-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65845317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthesizing evidence from clinical trials with dynamic interactive argument trees","authors":"Sanchez-Graillet, Olivia, Witte, Christian, Grimm, Frank, Grautoff, Steffen, Ell, Basil, Cimiano, Philipp","doi":"10.1186/s13326-022-00270-8","DOIUrl":"https://doi.org/10.1186/s13326-022-00270-8","url":null,"abstract":"Evidence-based medicine propagates that medical/clinical decisions are made by taking into account high-quality evidence, most notably in the form of randomized clinical trials. Evidence-based decision-making requires aggregating the evidence available in multiple trials to reach –by means of systematic reviews– a conclusive recommendation on which treatment is best suited for a given patient population. However, it is challenging to produce systematic reviews to keep up with the ever-growing number of published clinical trials. Therefore, new computational approaches are necessary to support the creation of systematic reviews that include the most up-to-date evidence.We propose a method to synthesize the evidence available in clinical trials in an ad-hoc and on-demand manner by automatically arranging such evidence in the form of a hierarchical argument that recommends a therapy as being superior to some other therapy along a number of key dimensions corresponding to the clinical endpoints of interest. The method has also been implemented as a web tool that allows users to explore the effects of excluding different points of evidence, and indicating relative preferences on the endpoints. Through two use cases, our method was shown to be able to generate conclusions similar to the ones of published systematic reviews. To evaluate our method implemented as a web tool, we carried out a survey and usability analysis with medical professionals. The results show that the tool was perceived as being valuable, acknowledging its potential to inform clinical decision-making and to complement the information from existing medical guidelines. The method presented is a simple but yet effective argumentation-based method that contributes to support the synthesis of clinical trial evidence. A current limitation of the method is that it relies on a manually populated knowledge base. This problem could be alleviated by deploying natural language processing methods to extract the relevant information from publications.","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":"22 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2022-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138538451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An annotated corpus of clinical trial publications supporting schema-based relational information extraction","authors":"Olivia Sanchez-Graillet, Christian Witte, Frank Grimm, P. Cimiano","doi":"10.1186/s13326-022-00271-7","DOIUrl":"https://doi.org/10.1186/s13326-022-00271-7","url":null,"abstract":"","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":" ","pages":""},"PeriodicalIF":1.9,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43016385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SemClinBr - a multi-institutional and multi-specialty semantically annotated corpus for Portuguese clinical NLP tasks.","authors":"Lucas Emanuel Silva E Oliveira,&nbsp;Ana Carolina Peters,&nbsp;Adalniza Moura Pucca da Silva,&nbsp;Caroline Pilatti Gebeluca,&nbsp;Yohan Bonescki Gumiel,&nbsp;Lilian Mie Mukai Cintho,&nbsp;Deborah Ribeiro Carvalho,&nbsp;Sadid Al Hasan,&nbsp;Claudia Maria Cabral Moro","doi":"10.1186/s13326-022-00269-1","DOIUrl":"https://doi.org/10.1186/s13326-022-00269-1","url":null,"abstract":"<p><strong>Background: </strong>The high volume of research focusing on extracting patient information from electronic health records (EHRs) has led to an increase in the demand for annotated corpora, which are a precious resource for both the development and evaluation of natural language processing (NLP) algorithms. The absence of a multipurpose clinical corpus outside the scope of the English language, especially in Brazilian Portuguese, is glaring and severely impacts scientific progress in the biomedical NLP field.</p><p><strong>Methods: </strong>In this study, a semantically annotated corpus was developed using clinical text from multiple medical specialties, document types, and institutions. In addition, we present, (1) a survey listing common aspects, differences, and lessons learned from previous research, (2) a fine-grained annotation schema that can be replicated to guide other annotation initiatives, (3) a web-based annotation tool focusing on an annotation suggestion feature, and (4) both intrinsic and extrinsic evaluation of the annotations.</p><p><strong>Results: </strong>This study resulted in SemClinBr, a corpus that has 1000 clinical notes, labeled with 65,117 entities and 11,263 relations. In addition, both negation cues and medical abbreviation dictionaries were generated from the annotations. The average annotator agreement score varied from 0.71 (applying strict match) to 0.92 (considering a relaxed match) while accepting partial overlaps and hierarchically related semantic types. The extrinsic evaluation, when applying the corpus to two downstream NLP tasks, demonstrated the reliability and usefulness of annotations, with the systems achieving results that were consistent with the agreement scores.</p><p><strong>Conclusion: </strong>The SemClinBr corpus and other resources produced in this work can support clinical NLP studies, providing a common development and evaluation resource for the research community, boosting the utilization of EHRs in both clinical practice and biomedical research. To the best of our knowledge, SemClinBr is the first available Portuguese clinical corpus.</p>","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":"13 1","pages":"13"},"PeriodicalIF":1.9,"publicationDate":"2022-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9080187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10252310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}