메뉴 건너뛰기




Volumn 16, Issue , 2016, Pages

Ensembles of randomized trees using diverse distributed representations of clinical events

Author keywords

Adverse drug events; Distributional semantics; Electronic health records; Heterogeneous data; Pharmacovigilance; Random forest

Indexed keywords

ADVERSE DRUG REACTION; DECISION TREE; DRUG SURVEILLANCE PROGRAM; ELECTRONIC HEALTH RECORD; HUMAN; MACHINE LEARNING; SEMANTICS; THEORETICAL MODEL;

EID: 84978923841     PISSN: None     EISSN: 14726947     Source Type: Journal    
DOI: 10.1186/s12911-016-0309-0     Document Type: Article
Times cited : (20)

References (49)
  • 1
    • 84861235431 scopus 로고    scopus 로고
    • Mining electronic health records: Towards better research applications and clinical care
    • 1:CAS:528:DC%2BC38XmtlGqtrY%3D 22549152
    • Jensen PB, Jensen LJ, Brunak S. Mining electronic health records: towards better research applications and clinical care. Nat Rev Genet. 2012; 13(6):395-405.
    • (2012) Nat Rev Genet , vol.13 , Issue.6 , pp. 395-405
    • Jensen, P.B.1    Jensen, L.J.2    Brunak, S.3
  • 4
    • 84898815541 scopus 로고    scopus 로고
    • Dose-specific adverse drug reaction identification in electronic patient records: Temporal data mining in an inpatient psychiatric population
    • 1:CAS:528:DC%2BC2cXls1Onsrc%3D 24634163 3975083
    • Eriksson R, Werge T, Jensen LJ, Brunak S. Dose-specific adverse drug reaction identification in electronic patient records: temporal data mining in an inpatient psychiatric population. Drug Saf. 2014; 37(4):237-47.
    • (2014) Drug Saf , vol.37 , Issue.4 , pp. 237-247
    • Eriksson, R.1    Werge, T.2    Jensen, L.J.3    Brunak, S.4
  • 5
    • 84924295546 scopus 로고    scopus 로고
    • Incorporating temporal ehr data in predictive models for risk stratification of renal function deterioration
    • 25460205
    • Singh A, Nadkarni G, Gottesman O, Ellis SB, Bottinger EP, Guttag JV. Incorporating temporal ehr data in predictive models for risk stratification of renal function deterioration. J Biomed Inform. 2015; 53:220-8.
    • (2015) J Biomed Inform , vol.53 , pp. 220-228
    • Singh, A.1    Nadkarni, G.2    Gottesman, O.3    Ellis, S.B.4    Bottinger, E.P.5    Guttag, J.V.6
  • 7
    • 84962373609 scopus 로고    scopus 로고
    • Temporal weighting of clinical events in electronic health records for pharmacovigilance
    • IEEE
    • Zhao J. Temporal weighting of clinical events in electronic health records for pharmacovigilance. In: IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE: 2015. p. 375-81.
    • (2015) IEEE International Conference on Bioinformatics and Biomedicine (BIBM) , pp. 375-381
    • Zhao, J.1
  • 8
    • 50649122567 scopus 로고    scopus 로고
    • Extracting information from textual documents in the electronic health record: A review of recent research
    • Meystre SM, Savova GK, Kipper-Schuler KC, Hurdle JF, et al. Extracting information from textual documents in the electronic health record: a review of recent research. Yearb Med Inform. 2008; 35:128-44.
    • (2008) Yearb Med Inform , vol.35 , pp. 128-144
    • Meystre, S.M.1    Savova, G.K.2    Kipper-Schuler, K.C.3    Hurdle, J.F.4
  • 9
    • 0035564886 scopus 로고    scopus 로고
    • Disambiguating ambiguous biomedical terms in biomedical narrative text: An unsupervised method
    • 1:STN:280:DC%2BD383jvFyruw%3D%3D 11977807
    • Liu H, Lussier YA, Friedman C. Disambiguating ambiguous biomedical terms in biomedical narrative text: an unsupervised method. J Biomed Inform. 2001; 34(4):249-61.
    • (2001) J Biomed Inform , vol.34 , Issue.4 , pp. 249-261
    • Liu, H.1    Lussier, Y.A.2    Friedman, C.3
  • 11
    • 0000679216 scopus 로고
    • Distributional structure
    • Harris ZS. Distributional structure. Word. 1954; 10(2-3):146-162.
    • (1954) Word , vol.10 , Issue.2-3 , pp. 146-162
    • Harris, Z.S.1
  • 12
    • 77952700189 scopus 로고    scopus 로고
    • From frequency to meaning: Vector space models of semantics
    • Turney PD, Pantel P, et al.From frequency to meaning: Vector space models of semantics. J Artif Intell Res. 2010; 37(1):141-88.
    • (2010) J Artif Intell Res , vol.37 , Issue.1 , pp. 141-188
    • Turney, P.D.1    Pantel, P.2
  • 13
    • 61949432274 scopus 로고    scopus 로고
    • Empirical distributional semantics: Methods and biomedical applications
    • 19232399 2750802
    • Cohen T, Widdows D. Empirical distributional semantics: methods and biomedical applications. J Biomed Inform. 2009; 42(2):390-405.
    • (2009) J Biomed Inform , vol.42 , Issue.2 , pp. 390-405
    • Cohen, T.1    Widdows, D.2
  • 18
  • 19
    • 84856376731 scopus 로고    scopus 로고
    • Enhancing clinical concept extraction with distributional semantics
    • 22085698
    • Jonnalagadda S, Cohen T, Wu S, Gonzalez G. Enhancing clinical concept extraction with distributional semantics. J Biomed Inform. 2012; 45(1):129-40.
    • (2012) J Biomed Inform , vol.45 , Issue.1 , pp. 129-140
    • Jonnalagadda, S.1    Cohen, T.2    Wu, S.3    Gonzalez, G.4
  • 21
    • 80052983616 scopus 로고    scopus 로고
    • Diagnosis Code Assignment Support Using Random Indexing of Patient Records - A Qualitative Feasibility Study
    • Springer Berlin/Heidelberg
    • Henriksson A, Hassel M, Kvist M. Diagnosis Code Assignment Support Using Random Indexing of Patient Records - A Qualitative Feasibility Study. In: Artificial Intelligence in Medicine. Berlin/Heidelberg: Springer: 2011. p. 348-52.
    • (2011) Artificial Intelligence in Medicine
    • Henriksson, A.1    Hassel, M.2    Kvist, M.3
  • 26
    • 84949514782 scopus 로고    scopus 로고
    • Identifying adverse drug event information in clinical notes with distributional semantic representations of context
    • 26291578
    • Henriksson A, Kvist M, Dalianis H, Duneld M. Identifying adverse drug event information in clinical notes with distributional semantic representations of context. J Biomed Inform. 2015; 57:333-49.
    • (2015) J Biomed Inform , vol.57 , pp. 333-349
    • Henriksson, A.1    Kvist, M.2    Dalianis, H.3    Duneld, M.4
  • 31
    • 84946740793 scopus 로고    scopus 로고
    • Learning multiple distributed prototypes of semantic categories for named entity recognition
    • Henriksson A. Learning multiple distributed prototypes of semantic categories for named entity recognition. Int J Data Min Bioinforma. 2015; 13(4):395-411.
    • (2015) Int J Data Min Bioinforma , vol.13 , Issue.4 , pp. 395-411
    • Henriksson, A.1
  • 34
    • 84946725881 scopus 로고    scopus 로고
    • A large scale evaluation of distributional semantic models: Parameters, interactions and model selection
    • Lapesa G, Evert S. A large scale evaluation of distributional semantic models: parameters, interactions and model selection. Trans Asso Comput Linguis. 2014; 2:531-45.
    • (2014) Trans Asso Comput Linguis , vol.2 , pp. 531-545
    • Lapesa, G.1    Evert, S.2
  • 35
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman L. Random forests. Mach Learn. 2001; 45(1):5-32.
    • (2001) Mach Learn , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 36
    • 80053403826 scopus 로고    scopus 로고
    • Ensemble methods in machine learning
    • Springer Berlin/Heidelberg
    • Dietterich TG. Ensemble methods in machine learning. In: Multiple Classifier Systems. Berlin/Heidelberg: Springer: 2000. p. 1-15.
    • (2000) Multiple Classifier Systems
    • Dietterich, T.G.1
  • 37
    • 0030102652 scopus 로고    scopus 로고
    • Information aggregation, rationality, and the condorcet jury theorem
    • Austen-Smith D, Banks JS. Information aggregation, rationality, and the condorcet jury theorem. Am Polit Sci Rev. 1996; 90(01):34-45.
    • (1996) Am Polit Sci Rev , vol.90 , Issue.1 , pp. 34-45
    • Austen-Smith, D.1    Banks, J.S.2
  • 38
    • 0037403516 scopus 로고    scopus 로고
    • Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
    • Kuncheva LI, Whitaker CJ. Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy. Mach Learn. 2003; 51(2):181-207.
    • (2003) Mach Learn , vol.51 , Issue.2 , pp. 181-207
    • Kuncheva, L.I.1    Whitaker, C.J.2
  • 39
    • 85054435084 scopus 로고
    • Neural network ensembles, cross validation, and active learning
    • MIT Press Cambridge MA
    • Krogh A, Vedelsby J. Neural network ensembles, cross validation, and active learning. In: Advances in Neural Information Processing Systems. Cambridge MA: MIT Press: 1995. p. 231-8.
    • (1995) Advances in Neural Information Processing Systems
    • Krogh, A.1    Vedelsby, J.2
  • 41
    • 33646744337 scopus 로고    scopus 로고
    • Under-reporting of adverse drug reactions
    • 16689555
    • Hazell L, Shakir SA. Under-reporting of adverse drug reactions. Drug Saf. 2006; 29(5):385-96.
    • (2006) Drug Saf , vol.29 , Issue.5 , pp. 385-396
    • Hazell, L.1    Shakir, S.A.2
  • 42
    • 85083951332 scopus 로고    scopus 로고
    • Efficient estimation of word representations in vector space
    • arXiv
    • Mikolov T, Chen K, Corrado G, Dean J. Efficient estimation of word representations in vector space. In: ICLR Worshop. arXiv: 2013.
    • (2013) ICLR Worshop
    • Mikolov, T.1    Chen, K.2    Corrado, G.3    Dean, J.4
  • 45
    • 38049036817 scopus 로고    scopus 로고
    • Combining bagging and random subspaces to create better ensembles
    • Springer Berlin/Heidelberg
    • Panov P, Džeroski S. Combining bagging and random subspaces to create better ensembles. In: Proceedings of Symposium on Intelligent Data Analysis. Berlin/Heidelberg: Springer: 2007. p. 118-29.
    • (2007) Proceedings of Symposium on Intelligent Data Analysis
    • Panov, P.1    Džeroski, S.2
  • 47
    • 79957471572 scopus 로고    scopus 로고
    • Drug-related admissions and hospital-acquired adverse drug events in Germany: A longitudinal analysis from 2003 to 2007 of icd-10-coded routine data
    • 21619706 3116475
    • Stausberg J, Hasford J. Drug-related admissions and hospital-acquired adverse drug events in germany: a longitudinal analysis from 2003 to 2007 of icd-10-coded routine data. BMC Health Serv Res. 2011; 11(1):134.
    • (2011) BMC Health Serv Res , vol.11 , Issue.1 , pp. 134
    • Stausberg, J.1    Hasford, J.2
  • 48
    • 84906736226 scopus 로고    scopus 로고
    • Stagger: An open-source part of speech tagger for swedish
    • Östling R. Stagger: an open-source part of speech tagger for swedish. North Eur J Lang Technol (NEJLT). 2013; 3:1-18.
    • (2013) North Eur J Lang Technol (NEJLT) , vol.3 , pp. 1-18
    • Östling, R.1
  • 49
    • 58149287952 scopus 로고    scopus 로고
    • An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons
    • Garcia S, Herrera F. An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons. J Mach Learn Res. 2008; 9(12):2677-2694.
    • (2008) J Mach Learn Res , vol.9 , Issue.12 , pp. 2677-2694
    • Garcia, S.1    Herrera, F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.