FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4210806126> ?p ?o ?g. }

• W4210806126 abstract "<sec> <title>BACKGROUND</title> 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. </sec> <sec> <title>OBJECTIVE</title> The aim of this study was to automatically construct and evaluate expanded PubMed queries of the form <i>“preferred term”[MH] OR “preferred term”[TIAB] OR “synonym 1”[TIAB] OR “synonym 2”[TIAB] OR …,</i> for each of the 28,313 Medical Subject Heading (MeSH) descriptors, by using different semantic expansion strategies. We sought to propose an innovative method that could automatically evaluate these strategies, based on the three main metrics used in information science (precision, recall, and F-measure). </sec> <sec> <title>METHODS</title> Three semantic expansion strategies were assessed. They differed by the synonyms used to build the queries as follows: MeSH synonyms, Unified Medical Language System (UMLS) mappings, and custom mappings (Catalogue et Index des Sites Médicaux de langue Française [CISMeF]). The precision, recall, and F-measure metrics were automatically computed for the three strategies and for the standard automatic term mapping (ATM) of PubMed. The method to automatically compute the metrics involved computing the number of all relevant citations (A), using National Library of Medicine indexing as the gold standard (<i>“preferred term”[MH]</i>), the number of citations retrieved by the added terms (<i>”synonym 1“[TIAB] OR ”synonym 2“[TIAB] OR …</i>) (B), and the number of relevant citations retrieved by the added terms (combining the previous two queries with an “AND” operator) (C). It was possible to programmatically compute the metrics for each strategy using each of the 28,313 MeSH descriptors as a “preferred term,” corresponding to 239,724 different queries built and sent to the PubMed application program interface. The four search strategies were ranked and compared for each metric. </sec> <sec> <title>RESULTS</title> ATM had the worst performance for all three metrics among the four strategies. The MeSH strategy had the best mean precision (51%, SD 23%). The UMLS strategy had the best recall and F-measure (41%, SD 31% and 36%, SD 24%, respectively). CISMeF had the second best recall and F-measure (40%, SD 31% and 35%, SD 24%, respectively). However, considering a cutoff of 5%, CISMeF had better precision than UMLS for 1180 descriptors, better recall for 793 descriptors, and better F-measure for 678 descriptors. </sec> <sec> <title>CONCLUSIONS</title> This study highlights the importance of using semantic expansion strategies to improve information retrieval. However, the performances of a given strategy, relatively to another, varied greatly depending on the MeSH descriptor. These results confirm there is no ideal search strategy for all descriptors. Different semantic expansions should be used depending on the descriptor and the user’s objectives. Thus, we developed an interface that allows users to input a descriptor and then proposes the best semantic expansion to maximize the three main metrics (precision, recall, and F-measure). </sec>" @default.
• W4210806126 created "2022-02-08" @default.
• W4210806126 creator A5004593070 @default.
• W4210806126 creator A5015805321 @default.
• W4210806126 creator A5061941257 @default.
• W4210806126 creator A5082866319 @default.
• W4210806126 creator A5024343637 @default.
• W4210806126 creator A5048497169 @default.
• W4210806126 date "2018-11-12" @default.
• W4210806126 modified "2023-09-27" @default.
• W4210806126 title "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 (Preprint)" @default.
• W4210806126 cites W1976829395 @default.
• W4210806126 cites W2008368750 @default.
• W4210806126 cites W2013410366 @default.
• W4210806126 cites W2033176810 @default.
• W4210806126 cites W2039278176 @default.
• W4210806126 cites W2098146716 @default.
• W4210806126 cites W2099791390 @default.
• W4210806126 cites W2102169654 @default.
• W4210806126 doi "https://doi.org/10.2196/preprints.12799" @default.
• W4210806126 hasPublicationYear "2018" @default.
• W4210806126 type Work @default.
• W4210806126 citedByCount "0" @default.
• W4210806126 crossrefType "posted-content" @default.
• W4210806126 hasAuthorship W4210806126A5004593070 @default.
• W4210806126 hasAuthorship W4210806126A5015805321 @default.
• W4210806126 hasAuthorship W4210806126A5024343637 @default.
• W4210806126 hasAuthorship W4210806126A5048497169 @default.
• W4210806126 hasAuthorship W4210806126A5061941257 @default.
• W4210806126 hasAuthorship W4210806126A5082866319 @default.
• W4210806126 hasBestOaLocation W42108061262 @default.
• W4210806126 hasConcept C121332964 @default.
• W4210806126 hasConcept C124101348 @default.
• W4210806126 hasConcept C13280743 @default.
• W4210806126 hasConcept C136764020 @default.
• W4210806126 hasConcept C157369684 @default.
• W4210806126 hasConcept C173483453 @default.
• W4210806126 hasConcept C184337299 @default.
• W4210806126 hasConcept C199360897 @default.
• W4210806126 hasConcept C204321447 @default.
• W4210806126 hasConcept C205649164 @default.
• W4210806126 hasConcept C23123220 @default.
• W4210806126 hasConcept C2776937971 @default.
• W4210806126 hasConcept C2777382242 @default.
• W4210806126 hasConcept C2777855551 @default.
• W4210806126 hasConcept C2780009758 @default.
• W4210806126 hasConcept C2780801425 @default.
• W4210806126 hasConcept C41008148 @default.
• W4210806126 hasConcept C59822182 @default.
• W4210806126 hasConcept C61797465 @default.
• W4210806126 hasConcept C62520636 @default.
• W4210806126 hasConcept C69505689 @default.
• W4210806126 hasConcept C75165309 @default.
• W4210806126 hasConcept C81669768 @default.
• W4210806126 hasConcept C86803240 @default.
• W4210806126 hasConceptScore W4210806126C121332964 @default.
• W4210806126 hasConceptScore W4210806126C124101348 @default.
• W4210806126 hasConceptScore W4210806126C13280743 @default.
• W4210806126 hasConceptScore W4210806126C136764020 @default.
• W4210806126 hasConceptScore W4210806126C157369684 @default.
• W4210806126 hasConceptScore W4210806126C173483453 @default.
• W4210806126 hasConceptScore W4210806126C184337299 @default.
• W4210806126 hasConceptScore W4210806126C199360897 @default.
• W4210806126 hasConceptScore W4210806126C204321447 @default.
• W4210806126 hasConceptScore W4210806126C205649164 @default.
• W4210806126 hasConceptScore W4210806126C23123220 @default.
• W4210806126 hasConceptScore W4210806126C2776937971 @default.
• W4210806126 hasConceptScore W4210806126C2777382242 @default.
• W4210806126 hasConceptScore W4210806126C2777855551 @default.
• W4210806126 hasConceptScore W4210806126C2780009758 @default.
• W4210806126 hasConceptScore W4210806126C2780801425 @default.
• W4210806126 hasConceptScore W4210806126C41008148 @default.
• W4210806126 hasConceptScore W4210806126C59822182 @default.
• W4210806126 hasConceptScore W4210806126C61797465 @default.
• W4210806126 hasConceptScore W4210806126C62520636 @default.
• W4210806126 hasConceptScore W4210806126C69505689 @default.
• W4210806126 hasConceptScore W4210806126C75165309 @default.
• W4210806126 hasConceptScore W4210806126C81669768 @default.
• W4210806126 hasConceptScore W4210806126C86803240 @default.
• W4210806126 hasLocation W42108061261 @default.
• W4210806126 hasLocation W42108061262 @default.
• W4210806126 hasOpenAccess W4210806126 @default.
• W4210806126 hasPrimaryLocation W42108061261 @default.
• W4210806126 hasRelatedWork W137965669 @default.
• W4210806126 hasRelatedWork W1485918728 @default.
• W4210806126 hasRelatedWork W1517188135 @default.
• W4210806126 hasRelatedWork W1568553947 @default.
• W4210806126 hasRelatedWork W1568866260 @default.
• W4210806126 hasRelatedWork W1994929347 @default.
• W4210806126 hasRelatedWork W2056491647 @default.
• W4210806126 hasRelatedWork W2168191173 @default.
• W4210806126 hasRelatedWork W3014082802 @default.
• W4210806126 hasRelatedWork W4210806126 @default.
• W4210806126 isParatext "false" @default.
• W4210806126 isRetracted "false" @default.
• W4210806126 workType "article" @default.