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Journal of Digital Imaging

, Volume 26, Issue 4, pp 709–713 | Cite as

Automatic Retrieval of Bone Fracture Knowledge Using Natural Language Processing

  • Bao H. DoEmail author
  • Andrew S. Wu
  • Joan Maley
  • Sandip Biswal
Article

Abstract

Natural language processing (NLP) techniques to extract data from unstructured text into formal computer representations are valuable for creating robust, scalable methods to mine data in medical documents and radiology reports. As voice recognition (VR) becomes more prevalent in radiology practice, there is opportunity for implementing NLP in real time for decision-support applications such as context-aware information retrieval. For example, as the radiologist dictates a report, an NLP algorithm can extract concepts from the text and retrieve relevant classification or diagnosis criteria or calculate disease probability. NLP can work in parallel with VR to potentially facilitate evidence-based reporting (for example, automatically retrieving the Bosniak classification when the radiologist describes a kidney cyst). For these reasons, we developed and validated an NLP system which extracts fracture and anatomy concepts from unstructured text and retrieves relevant bone fracture knowledge. We implement our NLP in an HTML5 web application to demonstrate a proof-of-concept feedback NLP system which retrieves bone fracture knowledge in real time.

Keywords

Natural language processing Decision support Information retrieval of bone fractures 

Notes

Acknowledgment of Grants

None

Financial Disclosures or Other Assistance

None

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Copyright information

© Society for Imaging Informatics in Medicine 2012

Authors and Affiliations

  • Bao H. Do
    • 1
    • 4
    Email author
  • Andrew S. Wu
    • 2
  • Joan Maley
    • 3
  • Sandip Biswal
    • 1
  1. 1.Division of Musculoskeletal Section, Department of RadiologyStanford University School of MedicineStanfordUSA
  2. 2.Department of RadiologyKaiser Permanente Downey Medical CenterDowneyUSA
  3. 3.Division of Neuroradiology, Department of RadiologyUniversity of IowaIowa CityUSA
  4. 4.Division of Musculoskeletal Imaging, Department of RadiologyStanford University Medical CenterStanfordUSA

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