FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2891466669> ?p ?o ?g. }

• W2891466669 endingPage "109" @default.
• W2891466669 startingPage "98" @default.
• W2891466669 abstract "To develop a framework to incorporate background domain knowledge into classification rule learning for knowledge discovery in biomedicine.Bayesian rule learning (BRL) is a rule-based classifier that uses a greedy best-first search over a space of Bayesian belief-networks (BN) to find the optimal BN to explain the input dataset, and then infers classification rules from this BN. BRL uses a Bayesian score to evaluate the quality of BNs. In this paper, we extended the Bayesian score to include informative structure priors, which encodes our prior domain knowledge about the dataset. We call this extension of BRL as BRLp. The structure prior has a λ hyperparameter that allows the user to tune the degree of incorporation of the prior knowledge in the model learning process. We studied the effect of λ on model learning using a simulated dataset and a real-world lung cancer prognostic biomarker dataset, by measuring the degree of incorporation of our specified prior knowledge. We also monitored its effect on the model predictive performance. Finally, we compared BRLp to other state-of-the-art classifiers commonly used in biomedicine.We evaluated the degree of incorporation of prior knowledge into BRLp, with simulated data by measuring the Graph Edit Distance between the true data-generating model and the model learned by BRLp. We specified the true model using informative structure priors. We observed that by increasing the value of λ we were able to increase the influence of the specified structure priors on model learning. A large value of λ of BRLp caused it to return the true model. This also led to a gain in predictive performance measured by area under the receiver operator characteristic curve (AUC). We then obtained a publicly available real-world lung cancer prognostic biomarker dataset and specified a known biomarker from literature [the epidermal growth factor receptor (EGFR) gene]. We again observed that larger values of λ led to an increased incorporation of EGFR into the final BRLp model. This relevant background knowledge also led to a gain in AUC.BRLp enables tunable structure priors to be incorporated during Bayesian classification rule learning that integrates data and knowledge as demonstrated using lung cancer biomarker data." @default.
• W2891466669 created "2018-09-27" @default.
• W2891466669 creator A5041874845 @default.
• W2891466669 creator A5069347895 @default.
• W2891466669 date "2018-09-14" @default.
• W2891466669 modified "2023-10-16" @default.
• W2891466669 title "Tunable structure priors for Bayesian rule learning for knowledge integrated biomarker discovery" @default.
• W2891466669 cites W1495374327 @default.
• W2891466669 cites W1512098439 @default.
• W2891466669 cites W1547246444 @default.
• W2891466669 cites W1670263352 @default.
• W2891466669 cites W1837617056 @default.
• W2891466669 cites W1928201966 @default.
• W2891466669 cites W1967411964 @default.
• W2891466669 cites W2007022163 @default.
• W2891466669 cites W2087264237 @default.
• W2891466669 cites W2114127539 @default.
• W2891466669 cites W2116634113 @default.
• W2891466669 cites W2118258530 @default.
• W2891466669 cites W2118423420 @default.
• W2891466669 cites W2143859186 @default.
• W2891466669 cites W2154293840 @default.
• W2891466669 cites W2506039404 @default.
• W2891466669 cites W2575354640 @default.
• W2891466669 cites W2911964244 @default.
• W2891466669 doi "https://doi.org/10.5306/wjco.v9.i5.98" @default.
• W2891466669 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6153126" @default.
• W2891466669 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30254965" @default.
• W2891466669 hasPublicationYear "2018" @default.
• W2891466669 type Work @default.
• W2891466669 sameAs 2891466669 @default.
• W2891466669 citedByCount "2" @default.
• W2891466669 countsByYear W28914666692019 @default.
• W2891466669 countsByYear W28914666692020 @default.
• W2891466669 crossrefType "journal-article" @default.
• W2891466669 hasAuthorship W2891466669A5041874845 @default.
• W2891466669 hasAuthorship W2891466669A5069347895 @default.
• W2891466669 hasBestOaLocation W28914666691 @default.
• W2891466669 hasConcept C107673813 @default.
• W2891466669 hasConcept C119857082 @default.
• W2891466669 hasConcept C124101348 @default.
• W2891466669 hasConcept C154945302 @default.
• W2891466669 hasConcept C160234255 @default.
• W2891466669 hasConcept C177769412 @default.
• W2891466669 hasConcept C207685749 @default.
• W2891466669 hasConcept C41008148 @default.
• W2891466669 hasConcept C8642999 @default.
• W2891466669 hasConcept C95623464 @default.
• W2891466669 hasConceptScore W2891466669C107673813 @default.
• W2891466669 hasConceptScore W2891466669C119857082 @default.
• W2891466669 hasConceptScore W2891466669C124101348 @default.
• W2891466669 hasConceptScore W2891466669C154945302 @default.
• W2891466669 hasConceptScore W2891466669C160234255 @default.
• W2891466669 hasConceptScore W2891466669C177769412 @default.
• W2891466669 hasConceptScore W2891466669C207685749 @default.
• W2891466669 hasConceptScore W2891466669C41008148 @default.
• W2891466669 hasConceptScore W2891466669C8642999 @default.
• W2891466669 hasConceptScore W2891466669C95623464 @default.
• W2891466669 hasIssue "5" @default.
• W2891466669 hasLocation W28914666691 @default.
• W2891466669 hasLocation W28914666692 @default.
• W2891466669 hasLocation W28914666693 @default.
• W2891466669 hasLocation W28914666694 @default.
• W2891466669 hasOpenAccess W2891466669 @default.
• W2891466669 hasPrimaryLocation W28914666691 @default.
• W2891466669 hasRelatedWork W2891466669 @default.
• W2891466669 hasRelatedWork W3001003127 @default.
• W2891466669 hasRelatedWork W4210794429 @default.
• W2891466669 hasRelatedWork W4223456145 @default.
• W2891466669 hasRelatedWork W4284971654 @default.
• W2891466669 hasRelatedWork W4292122269 @default.
• W2891466669 hasRelatedWork W4295309597 @default.
• W2891466669 hasRelatedWork W4309113015 @default.
• W2891466669 hasRelatedWork W4311832880 @default.
• W2891466669 hasRelatedWork W4382724518 @default.
• W2891466669 hasVolume "9" @default.
• W2891466669 isParatext "false" @default.
• W2891466669 isRetracted "false" @default.
• W2891466669 magId "2891466669" @default.
• W2891466669 workType "article" @default.