Matches in SemOpenAlex for { <https://semopenalex.org/work/W2124996938> ?p ?o ?g. }
- W2124996938 endingPage "1019" @default.
- W2124996938 startingPage "1009" @default.
- W2124996938 abstract "Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxes. Moreover, training data for these automated approaches at often sparsely annotated at best. The authors target unsupervised learning for modeling clinical narrative text, aiming at improving both accuracy and interpretability.The authors introduce a novel framework named subgraph augmented non-negative tensor factorization (SANTF). In addition to relying on atomic features (e.g., words in clinical narrative text), SANTF automatically mines higher-order features (e.g., relations of lymphoid cells expressing antigens) from clinical narrative text by converting sentences into a graph representation and identifying important subgraphs. The authors compose a tensor using patients, higher-order features, and atomic features as its respective modes. We then apply non-negative tensor factorization to cluster patients, and simultaneously identify latent groups of higher-order features that link to patient clusters, as in clinical guidelines where a panel of immunophenotypic features and laboratory results are used to specify diagnostic criteria.SANTF demonstrated over 10% improvement in averaged F-measure on patient clustering compared to widely used non-negative matrix factorization (NMF) and k-means clustering methods. Multiple baselines were established by modeling patient data using patient-by-features matrices with different feature configurations and then performing NMF or k-means to cluster patients. Feature analysis identified latent groups of higher-order features that lead to medical insights. We also found that the latent groups of atomic features help to better correlate the latent groups of higher-order features." @default.
- W2124996938 created "2016-06-24" @default.
- W2124996938 creator A5003076238 @default.
- W2124996938 creator A5006650843 @default.
- W2124996938 creator A5035186913 @default.
- W2124996938 creator A5049731469 @default.
- W2124996938 creator A5070926324 @default.
- W2124996938 creator A5084810789 @default.
- W2124996938 date "2015-04-09" @default.
- W2124996938 modified "2023-10-10" @default.
- W2124996938 title "Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text" @default.
- W2124996938 cites W1599615952 @default.
- W2124996938 cites W1902027874 @default.
- W2124996938 cites W1963826206 @default.
- W2124996938 cites W1968154520 @default.
- W2124996938 cites W1973825638 @default.
- W2124996938 cites W1978469053 @default.
- W2124996938 cites W1985644065 @default.
- W2124996938 cites W1988386518 @default.
- W2124996938 cites W2001082470 @default.
- W2124996938 cites W2004734764 @default.
- W2124996938 cites W2006454222 @default.
- W2124996938 cites W2009202077 @default.
- W2124996938 cites W2014426141 @default.
- W2124996938 cites W2024165284 @default.
- W2124996938 cites W2056967673 @default.
- W2124996938 cites W2064208261 @default.
- W2124996938 cites W2064299012 @default.
- W2124996938 cites W2073844507 @default.
- W2124996938 cites W2079196839 @default.
- W2124996938 cites W2092423825 @default.
- W2124996938 cites W2099694394 @default.
- W2124996938 cites W2101815756 @default.
- W2124996938 cites W2109317245 @default.
- W2124996938 cites W2110509222 @default.
- W2124996938 cites W2113359929 @default.
- W2124996938 cites W2120077398 @default.
- W2124996938 cites W2126552798 @default.
- W2124996938 cites W2136787567 @default.
- W2124996938 cites W2139865360 @default.
- W2124996938 cites W2150926065 @default.
- W2124996938 cites W2152061559 @default.
- W2124996938 cites W2154790710 @default.
- W2124996938 cites W2159636537 @default.
- W2124996938 cites W2165685007 @default.
- W2124996938 cites W2170516178 @default.
- W2124996938 cites W2173884055 @default.
- W2124996938 cites W4213009331 @default.
- W2124996938 cites W4230962320 @default.
- W2124996938 cites W67471658 @default.
- W2124996938 cites W73198697 @default.
- W2124996938 doi "https://doi.org/10.1093/jamia/ocv016" @default.
- W2124996938 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4986663" @default.
- W2124996938 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25862765" @default.
- W2124996938 hasPublicationYear "2015" @default.
- W2124996938 type Work @default.
- W2124996938 sameAs 2124996938 @default.
- W2124996938 citedByCount "50" @default.
- W2124996938 countsByYear W21249969382015 @default.
- W2124996938 countsByYear W21249969382016 @default.
- W2124996938 countsByYear W21249969382017 @default.
- W2124996938 countsByYear W21249969382018 @default.
- W2124996938 countsByYear W21249969382019 @default.
- W2124996938 countsByYear W21249969382020 @default.
- W2124996938 countsByYear W21249969382021 @default.
- W2124996938 countsByYear W21249969382022 @default.
- W2124996938 countsByYear W21249969382023 @default.
- W2124996938 crossrefType "journal-article" @default.
- W2124996938 hasAuthorship W2124996938A5003076238 @default.
- W2124996938 hasAuthorship W2124996938A5006650843 @default.
- W2124996938 hasAuthorship W2124996938A5035186913 @default.
- W2124996938 hasAuthorship W2124996938A5049731469 @default.
- W2124996938 hasAuthorship W2124996938A5070926324 @default.
- W2124996938 hasAuthorship W2124996938A5084810789 @default.
- W2124996938 hasBestOaLocation W21249969381 @default.
- W2124996938 hasConcept C119857082 @default.
- W2124996938 hasConcept C121332964 @default.
- W2124996938 hasConcept C124101348 @default.
- W2124996938 hasConcept C138885662 @default.
- W2124996938 hasConcept C152671427 @default.
- W2124996938 hasConcept C153180895 @default.
- W2124996938 hasConcept C154945302 @default.
- W2124996938 hasConcept C155281189 @default.
- W2124996938 hasConcept C158693339 @default.
- W2124996938 hasConcept C202444582 @default.
- W2124996938 hasConcept C204321447 @default.
- W2124996938 hasConcept C23123220 @default.
- W2124996938 hasConcept C2776401178 @default.
- W2124996938 hasConcept C2781067378 @default.
- W2124996938 hasConcept C33923547 @default.
- W2124996938 hasConcept C41008148 @default.
- W2124996938 hasConcept C41895202 @default.
- W2124996938 hasConcept C42355184 @default.
- W2124996938 hasConcept C48044578 @default.
- W2124996938 hasConcept C62520636 @default.
- W2124996938 hasConcept C73555534 @default.
- W2124996938 hasConcept C77088390 @default.
- W2124996938 hasConceptScore W2124996938C119857082 @default.