Skip to main content

2018 | OriginalPaper | Buchkapitel

MKDS: A Medical Knowledge Discovery System Learned from Electronic Medical Records (Demonstration)

verfasst von : Hen-Hsen Huang, An-Zi Yen, Hsin-Hsi Chen

Erschienen in: Information Retrieval Technology

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper presents a medical knowledge discovery system (MKDS) that learns the medical knowledge from electronic medical records (EMRs). The distributed word representations model the relations among medical concepts such as diseases and medicines. Four tasks, including spell checking, clinical trait extraction, analogical reasoning, and computer-aided diagnosis, are demonstrated in our system.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Bejan, C.A., Vanderwende, L., Wurfel, M.M., Yetisgen-Yildiz, M.: Assessing pneumonia identification from time-ordered narrative reports. In: Proceedings of 2012 AMIA Annual Symposium, pp. 1119–1128 (2012) Bejan, C.A., Vanderwende, L., Wurfel, M.M., Yetisgen-Yildiz, M.: Assessing pneumonia identification from time-ordered narrative reports. In: Proceedings of 2012 AMIA Annual Symposium, pp. 1119–1128 (2012)
2.
Zurück zum Zitat Davis, M.F., Sriram, S., Bush, W.S., Denny, J.C., Haines, J.L.: Automated extraction of clinical traits of multiple sclerosis in electronic medical records. J. Am. Med. Inform. Assoc. 20(2), 334–340 (2013)CrossRef Davis, M.F., Sriram, S., Bush, W.S., Denny, J.C., Haines, J.L.: Automated extraction of clinical traits of multiple sclerosis in electronic medical records. J. Am. Med. Inform. Assoc. 20(2), 334–340 (2013)CrossRef
3.
Zurück zum Zitat Demner-Fushman, D., Chapman, W.W., McDonald, C.J.: What can natural language processing do for clinical decision support? J. Biomed. Inform. 42(5), 760–772 (2009)CrossRef Demner-Fushman, D., Chapman, W.W., McDonald, C.J.: What can natural language processing do for clinical decision support? J. Biomed. Inform. 42(5), 760–772 (2009)CrossRef
4.
Zurück zum Zitat Hripcsak, G., Albers, D.J.: Next-generation phenotyping of electronic health records. J. Am. Med. Inform. Assoc. 20(1), 117–121 (2013)CrossRef Hripcsak, G., Albers, D.J.: Next-generation phenotyping of electronic health records. J. Am. Med. Inform. Assoc. 20(1), 117–121 (2013)CrossRef
6.
Zurück zum Zitat Kim, Y., Riloff, E., Meystre, S.M.: Improving classification of medical assertions in clinical notes. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL): Short Papers, pp. 311–316 (2011) Kim, Y., Riloff, E., Meystre, S.M.: Improving classification of medical assertions in clinical notes. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL): Short Papers, pp. 311–316 (2011)
7.
Zurück zum Zitat Levy, O., Goldberg, Y.: Linguistic regularities in sparse and explicit word representations. In: Proceedings of the 18th Conference on Computational Language Learning, pp. 171–180 (2014) Levy, O., Goldberg, Y.: Linguistic regularities in sparse and explicit word representations. In: Proceedings of the 18th Conference on Computational Language Learning, pp. 171–180 (2014)
8.
Zurück zum Zitat Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. In: ICLR Workshop Papers (2013) Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. In: ICLR Workshop Papers (2013)
9.
Zurück zum Zitat Mikolov, T., Yih, W.T., Zweig, G.: Linguistic regularities in continuous space word representations. In: Proceedings of NAACL-HLT, pp. 746–751 (2013) Mikolov, T., Yih, W.T., Zweig, G.: Linguistic regularities in continuous space word representations. In: Proceedings of NAACL-HLT, pp. 746–751 (2013)
10.
Zurück zum Zitat Pathak, J., Kho, A.N., Denny, J.C.: Electronic health records-driven phenotyping: challenges, recent advances, and perspectives. J. Am. Med. Inform. Assoc. 20(e2), e206–e211 (2013)CrossRef Pathak, J., Kho, A.N., Denny, J.C.: Electronic health records-driven phenotyping: challenges, recent advances, and perspectives. J. Am. Med. Inform. Assoc. 20(e2), e206–e211 (2013)CrossRef
11.
Zurück zum Zitat Shivade, C., et al.: A review of approaches to identifying patient phenotype cohorts using electronic health records. J. Am. Med. Inform. Assoc. 21, 221–230 (2014)CrossRef Shivade, C., et al.: A review of approaches to identifying patient phenotype cohorts using electronic health records. J. Am. Med. Inform. Assoc. 21, 221–230 (2014)CrossRef
12.
Zurück zum Zitat Stubbs, A., Kotfila, C., Xu, H., Uzuner, Ö.: Identifying risk factors for heart disease over time: overview of 2014 i2b2/UTHealth shared task track 2. J. Biomed. Inform. 58, S67–S77 (2015)CrossRef Stubbs, A., Kotfila, C., Xu, H., Uzuner, Ö.: Identifying risk factors for heart disease over time: overview of 2014 i2b2/UTHealth shared task track 2. J. Biomed. Inform. 58, S67–S77 (2015)CrossRef
13.
Zurück zum Zitat Sun, W., Rumshisky, A., Uzuner, O.: Evaluating temporal relations in clinical text: 2012 i2b2 challenge. J. Am. Med. Inform. Assoc. 20(5), 806–813 (2013)CrossRef Sun, W., Rumshisky, A., Uzuner, O.: Evaluating temporal relations in clinical text: 2012 i2b2 challenge. J. Am. Med. Inform. Assoc. 20(5), 806–813 (2013)CrossRef
14.
Zurück zum Zitat Uzuner, O., Bodnari, A., Shen, S., Forbush, T., Pestian, J., South, B.R.: Evaluating the state of the art in coreference resolution for electronic medical records. J. Am. Med. Inform. Assoc. 19(5), 786–791 (2012)CrossRef Uzuner, O., Bodnari, A., Shen, S., Forbush, T., Pestian, J., South, B.R.: Evaluating the state of the art in coreference resolution for electronic medical records. J. Am. Med. Inform. Assoc. 19(5), 786–791 (2012)CrossRef
15.
Zurück zum Zitat De Vine, L., Kholghi, M., Zuccon, G., Sitbon, L., Nguyen, A.: Analysis of word embeddings and sequence features for clinical information extraction. In: Proceedings of the 13th Annual Workshop of the Australasian Language Technology Association (2015) De Vine, L., Kholghi, M., Zuccon, G., Sitbon, L., Nguyen, A.: Analysis of word embeddings and sequence features for clinical information extraction. In: Proceedings of the 13th Annual Workshop of the Australasian Language Technology Association (2015)
16.
Zurück zum Zitat Voorhees, E.M., Hersh, W.: Overview of the TREC 2012 medical records track. In: Proceedings of the 21st Text REtrieval Conference (2012) Voorhees, E.M., Hersh, W.: Overview of the TREC 2012 medical records track. In: Proceedings of the 21st Text REtrieval Conference (2012)
Metadaten
Titel
MKDS: A Medical Knowledge Discovery System Learned from Electronic Medical Records (Demonstration)
verfasst von
Hen-Hsen Huang
An-Zi Yen
Hsin-Hsi Chen
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-030-03520-4_19

Neuer Inhalt