FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2214448182> ?p ?o ?g. }

• W2214448182 endingPage "786" @default.
• W2214448182 startingPage "779" @default.
• W2214448182 abstract "Predicting outcomes to guide clinical care, decision making, and resource allocation is a challenging undertaking in chronic kidney disease (CKD). Many prediction models have been developed, but few have been appropriately externally validated and even fewer have been assessed to be usable in the clinical setting. This contributes to the currently infrequent use of existing prediction models. Patients with CKD are a particularly heterogeneous group with significant biological variability, making the development of useful prediction models even more challenging. This article explores the different challenges in the development, validation, and application of prediction models in CKD. We explore the notion that newer biomarkers offer potential for enhancing existing and future prediction models and that modern technology is an opportunity to make prediction models more accessible and less cumbersome to use in clinical practice. Despite the challenges associated with their development and implementation, clinical prediction models have the potential to be a powerful tool for clinicians, researchers, and policy makers alike." @default.
• W2214448182 created "2016-06-24" @default.
• W2214448182 creator A5034960417 @default.
• W2214448182 creator A5046130400 @default.
• W2214448182 creator A5054139638 @default.
• W2214448182 date "2016-05-01" @default.
• W2214448182 modified "2023-09-27" @default.
• W2214448182 title "Predicting Progression in CKD: Perspectives and Precautions" @default.
• W2214448182 cites W1964291837 @default.
• W2214448182 cites W1990540788 @default.
• W2214448182 cites W1991038577 @default.
• W2214448182 cites W1991742244 @default.
• W2214448182 cites W1995850259 @default.
• W2214448182 cites W2000270471 @default.
• W2214448182 cites W2002359955 @default.
• W2214448182 cites W2010710496 @default.
• W2214448182 cites W2020323928 @default.
• W2214448182 cites W2020460355 @default.
• W2214448182 cites W2030322782 @default.
• W2214448182 cites W2034530740 @default.
• W2214448182 cites W2045030989 @default.
• W2214448182 cites W2048717100 @default.
• W2214448182 cites W2051411536 @default.
• W2214448182 cites W2056976690 @default.
• W2214448182 cites W2062050844 @default.
• W2214448182 cites W2068583723 @default.
• W2214448182 cites W2071727133 @default.
• W2214448182 cites W2073886650 @default.
• W2214448182 cites W2074769157 @default.
• W2214448182 cites W2080277228 @default.
• W2214448182 cites W2092433795 @default.
• W2214448182 cites W2094581349 @default.
• W2214448182 cites W2099760312 @default.
• W2214448182 cites W2110768118 @default.
• W2214448182 cites W2110843198 @default.
• W2214448182 cites W2116257995 @default.
• W2214448182 cites W2119910794 @default.
• W2214448182 cites W2124704085 @default.
• W2214448182 cites W2136065216 @default.
• W2214448182 cites W2136066105 @default.
• W2214448182 cites W2140468511 @default.
• W2214448182 cites W2140685775 @default.
• W2214448182 cites W2145632027 @default.
• W2214448182 cites W2146901169 @default.
• W2214448182 cites W2147888670 @default.
• W2214448182 cites W2148983669 @default.
• W2214448182 cites W2150578214 @default.
• W2214448182 cites W2151056789 @default.
• W2214448182 cites W2161595519 @default.
• W2214448182 cites W2165817472 @default.
• W2214448182 cites W4211214771 @default.
• W2214448182 cites W4233026002 @default.
• W2214448182 cites W4309358070 @default.
• W2214448182 doi "https://doi.org/10.1053/j.ajkd.2015.11.007" @default.
• W2214448182 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26725311" @default.
• W2214448182 hasPublicationYear "2016" @default.
• W2214448182 type Work @default.
• W2214448182 sameAs 2214448182 @default.
• W2214448182 citedByCount "19" @default.
• W2214448182 countsByYear W22144481822017 @default.
• W2214448182 countsByYear W22144481822019 @default.
• W2214448182 countsByYear W22144481822020 @default.
• W2214448182 countsByYear W22144481822021 @default.
• W2214448182 countsByYear W22144481822022 @default.
• W2214448182 countsByYear W22144481822023 @default.
• W2214448182 crossrefType "journal-article" @default.
• W2214448182 hasAuthorship W2214448182A5034960417 @default.
• W2214448182 hasAuthorship W2214448182A5046130400 @default.
• W2214448182 hasAuthorship W2214448182A5054139638 @default.
• W2214448182 hasConcept C112930515 @default.
• W2214448182 hasConcept C119857082 @default.
• W2214448182 hasConcept C126322002 @default.
• W2214448182 hasConcept C136764020 @default.
• W2214448182 hasConcept C162324750 @default.
• W2214448182 hasConcept C177713679 @default.
• W2214448182 hasConcept C1862650 @default.
• W2214448182 hasConcept C2522767166 @default.
• W2214448182 hasConcept C2778653478 @default.
• W2214448182 hasConcept C2779974597 @default.
• W2214448182 hasConcept C2780615836 @default.
• W2214448182 hasConcept C41008148 @default.
• W2214448182 hasConcept C45804977 @default.
• W2214448182 hasConcept C539667460 @default.
• W2214448182 hasConcept C71924100 @default.
• W2214448182 hasConceptScore W2214448182C112930515 @default.
• W2214448182 hasConceptScore W2214448182C119857082 @default.
• W2214448182 hasConceptScore W2214448182C126322002 @default.
• W2214448182 hasConceptScore W2214448182C136764020 @default.
• W2214448182 hasConceptScore W2214448182C162324750 @default.
• W2214448182 hasConceptScore W2214448182C177713679 @default.
• W2214448182 hasConceptScore W2214448182C1862650 @default.
• W2214448182 hasConceptScore W2214448182C2522767166 @default.
• W2214448182 hasConceptScore W2214448182C2778653478 @default.
• W2214448182 hasConceptScore W2214448182C2779974597 @default.
• W2214448182 hasConceptScore W2214448182C2780615836 @default.
• W2214448182 hasConceptScore W2214448182C41008148 @default.
• W2214448182 hasConceptScore W2214448182C45804977 @default.
• W2214448182 hasConceptScore W2214448182C539667460 @default.

• next