Entity linking of tweets based on dominant entity candidates

© 2018, Springer-Verlag GmbH Austria, part of Springer Nature. Entity linking, also known as semantic annotation, of textual content has received increasing attention. Recent works in this area have focused on entity linking on text with special characteristics such as search queries and tweets. The semantic annotation of tweets is specially proven to be challenging given the informal nature of the writing and the short length of the text. In this paper, we propose a method to perform entity linking on tweets built based on one primary hypothesis. We hypothesize that while there are formally many possible entity candidates for an ambiguous mention in a tweet, as listed on the disambiguation page of the corresponding entity on Wikipedia, there are only few entity candidates that are likely to be employed in the context of Twitter. Based on this hypothesis, we propose a method to identify such dominant entity candidates for each ambiguous mention and use them in the annotation process. Particularly, our proposed work integrates two phases (i) dominant entity candidate detection, which applies community detection methods for finding the dominant candidates of ambiguous mentions; and (ii) named entity disambiguation that links a tweet to entities in Wikipedia by only considering the identified dominant entity candidates. Our investigations show that: (1) there are only very few entity candidates for each ambiguous mention in a tweet that need to be considered when performing disambiguation. This helps us limit the candidate search space and hence noticeably reduce the entity linking time; (2) limiting the search space to only a subset of disambiguation options will not only improve entity linking execution time but will also lead to improved accuracy of the entity linking process when the main entity candidates of each mention are mined from a temporally aligned corpus. We show that our proposed method offers competitive results with the state-of-the-art methods in terms of precision and recall on widely used gold standard datasets while significantly reducing the time for processing each tweet

Shock wave lithotripsy, for the treatment of kidney stones, results in changes to routine blood tests and novel biomarkers: a prospective clinical pilot-study

From Springer Nature via Jisc Publications RouterHistory: received 2020-04-21, accepted 2020-05-27, registration 2020-05-27, pub-electronic 2020-06-01, online 2020-06-01, collection 2020-12Publication status: PublishedFunder: Institute of Biomedical Science; doi: http://dx.doi.org/10.13039/501100000825Abstract: Background: The number of patients undergoing shock wave lithotripsy (SWL) for kidney stones is increasing annually, and as such the development of post-operative complications, such as haematuria and acute kidney injury (AKI) following SWL, is likely to increase. The aim of the study was to evaluate changes in routine blood and novel biomarkers following SWL, for the treatment of kidney stones. Methods: Twelve patients undergoing SWL for solitary unilateral kidney stones were recruited. From patients (8 males and 4 females) aged between 31 and 72 years (median 43 years), venous blood samples were collected pre-operatively (baseline), at 30, 120 and 240 min post-operatively. Routine blood tests were performed using a Sysmex XE-5000, and Beckman Coulter AU5800 and AU680 analysers. NGAL, IL-18, IL-6, TNF-α, IL-10 and IL-8 concentrations were determined using commercially available ELISA kits. Results: Significant (p ≤ 0.05) changes were observed in several blood parameters following SWL. NGAL concentration significantly increased, with values peaking at 30 min post-treatment (p = 0.033). Although IL-18 concentration increased, these changes were not significant (p = 0.116). IL-6 revealed a statistically significant rise from pre-operative up to 4 h post-operatively (p 0.05). Conclusions: Changes to routine blood tests and specific biomarkers, in the future, may be more useful for clinicians. In turn, identification of a panel of biomarkers could provide valuable data on “normal” physiological response after lithotripsy. Ultimately, studies could be expanded to identify or predict those patients at increased risk of developing post-operative complications, such as acute kidney injury or. These studies, however, need validating involving larger cohorts