FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4383760666> ?p ?o ?g. }

• W4383760666 abstract "Abstract Background Recent advances in machine learning combined with the growing availability of digitized health records offer new opportunities for improving early diagnosis of depression. An emerging body of research shows that Electronic Health Records can be used to accurately predict cases of depression on the basis of individual’s primary care records. The successes of these studies are undeniable, but there is a growing concern that their results may not be replicable, which could cast doubt on their clinical usefulness. Methods To address this issue in the present paper, we set out to reproduce and replicate the work by Nichols et al. (2018), who trained predictive models of depression among young adults using Electronic Healthcare Records. Our contribution consists of three parts. First, we attempt to replicate the methodology used by the original authors, acquiring the same set of primary health records and reproducing their data processing and analysis. Second, we test models presented in the original paper on our own data, thus providing out of sample prediction of the predictive models. Third, we extend past work by considering several novel machine learning approaches in an attempt to improve the predictive accuracy achieved in the original work. Results In summary, our results demonstrate that the work of Nichols et al. is largely reproducible and replicable. This was the case both for the replication of the original model and the out of sample replication applying NRCBM coefficients to our new EHRs data. Although alternative predictive models did not improve model performance over standard logistic regression, our results indicate that stepwise variable selection is not stable even in the case of large data sets. Conclusion We discuss the challenges associated with the research on mental health and Electronic Health Records, including the need to produce interpretable and robust models. We demonstrated some potential issues associated with the reliance on EHRs, including changes in the regulations and guidelines (such as the QOF guidelines in the UK) and reliance on visits to GP as a predictor of specific disorders." @default.
• W4383760666 created "2023-07-11" @default.
• W4383760666 creator A5030631966 @default.
• W4383760666 creator A5035525398 @default.
• W4383760666 creator A5042648708 @default.
• W4383760666 creator A5072432368 @default.
• W4383760666 creator A5080890851 @default.
• W4383760666 date "2023-07-10" @default.
• W4383760666 modified "2023-09-26" @default.
• W4383760666 title "Replicability and reproducibility of predictive models for diagnosis of depression among young adults using Electronic Health Records" @default.
• W4383760666 cites W1993085080 @default.
• W4383760666 cites W2000993008 @default.
• W4383760666 cites W2019196399 @default.
• W4383760666 cites W2021944393 @default.
• W4383760666 cites W2031827511 @default.
• W4383760666 cites W2039156670 @default.
• W4383760666 cites W2052779929 @default.
• W4383760666 cites W2129925362 @default.
• W4383760666 cites W2155054485 @default.
• W4383760666 cites W2171340584 @default.
• W4383760666 cites W2317502704 @default.
• W4383760666 cites W2433046122 @default.
• W4383760666 cites W2508289190 @default.
• W4383760666 cites W2747454477 @default.
• W4383760666 cites W2886512263 @default.
• W4383760666 cites W2910254316 @default.
• W4383760666 cites W2924617106 @default.
• W4383760666 cites W2951648323 @default.
• W4383760666 cites W2966811678 @default.
• W4383760666 cites W2982634790 @default.
• W4383760666 cites W3010252321 @default.
• W4383760666 cites W3161588210 @default.
• W4383760666 cites W4296360598 @default.
• W4383760666 cites W4318577410 @default.
• W4383760666 doi "https://doi.org/10.21203/rs.3.rs-3104286/v1" @default.
• W4383760666 hasPublicationYear "2023" @default.
• W4383760666 type Work @default.
• W4383760666 citedByCount "0" @default.
• W4383760666 crossrefType "posted-content" @default.
• W4383760666 hasAuthorship W4383760666A5030631966 @default.
• W4383760666 hasAuthorship W4383760666A5035525398 @default.
• W4383760666 hasAuthorship W4383760666A5042648708 @default.
• W4383760666 hasAuthorship W4383760666A5072432368 @default.
• W4383760666 hasAuthorship W4383760666A5080890851 @default.
• W4383760666 hasBestOaLocation W43837606661 @default.
• W4383760666 hasConcept C105795698 @default.
• W4383760666 hasConcept C119857082 @default.
• W4383760666 hasConcept C12590798 @default.
• W4383760666 hasConcept C139719470 @default.
• W4383760666 hasConcept C151956035 @default.
• W4383760666 hasConcept C154945302 @default.
• W4383760666 hasConcept C160735492 @default.
• W4383760666 hasConcept C162324750 @default.
• W4383760666 hasConcept C177264268 @default.
• W4383760666 hasConcept C185592680 @default.
• W4383760666 hasConcept C198531522 @default.
• W4383760666 hasConcept C199360897 @default.
• W4383760666 hasConcept C2522767166 @default.
• W4383760666 hasConcept C2776867660 @default.
• W4383760666 hasConcept C2781162219 @default.
• W4383760666 hasConcept C3019952477 @default.
• W4383760666 hasConcept C3020144179 @default.
• W4383760666 hasConcept C33923547 @default.
• W4383760666 hasConcept C41008148 @default.
• W4383760666 hasConcept C43617362 @default.
• W4383760666 hasConcept C45804977 @default.
• W4383760666 hasConcept C50522688 @default.
• W4383760666 hasConcept C58489278 @default.
• W4383760666 hasConceptScore W4383760666C105795698 @default.
• W4383760666 hasConceptScore W4383760666C119857082 @default.
• W4383760666 hasConceptScore W4383760666C12590798 @default.
• W4383760666 hasConceptScore W4383760666C139719470 @default.
• W4383760666 hasConceptScore W4383760666C151956035 @default.
• W4383760666 hasConceptScore W4383760666C154945302 @default.
• W4383760666 hasConceptScore W4383760666C160735492 @default.
• W4383760666 hasConceptScore W4383760666C162324750 @default.
• W4383760666 hasConceptScore W4383760666C177264268 @default.
• W4383760666 hasConceptScore W4383760666C185592680 @default.
• W4383760666 hasConceptScore W4383760666C198531522 @default.
• W4383760666 hasConceptScore W4383760666C199360897 @default.
• W4383760666 hasConceptScore W4383760666C2522767166 @default.
• W4383760666 hasConceptScore W4383760666C2776867660 @default.
• W4383760666 hasConceptScore W4383760666C2781162219 @default.
• W4383760666 hasConceptScore W4383760666C3019952477 @default.
• W4383760666 hasConceptScore W4383760666C3020144179 @default.
• W4383760666 hasConceptScore W4383760666C33923547 @default.
• W4383760666 hasConceptScore W4383760666C41008148 @default.
• W4383760666 hasConceptScore W4383760666C43617362 @default.
• W4383760666 hasConceptScore W4383760666C45804977 @default.
• W4383760666 hasConceptScore W4383760666C50522688 @default.
• W4383760666 hasConceptScore W4383760666C58489278 @default.
• W4383760666 hasLocation W43837606661 @default.
• W4383760666 hasOpenAccess W4383760666 @default.
• W4383760666 hasPrimaryLocation W43837606661 @default.
• W4383760666 hasRelatedWork W2004792461 @default.
• W4383760666 hasRelatedWork W2518568468 @default.
• W4383760666 hasRelatedWork W2758561209 @default.
• W4383760666 hasRelatedWork W3000308030 @default.
• W4383760666 hasRelatedWork W3160244858 @default.
• W4383760666 hasRelatedWork W3208954537 @default.

• next