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Construction of a Knowledge Base for Empirical Knowledge in Neurosurgery

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Human-Computer Interaction. Interaction Techniques and Novel Applications (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12763))

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Abstract

Neurosurgeons accumulate a variety of empirical knowledge through surgeries. Post-operative reports, incident reports, and accident reports are effective means of recording and sharing empirical knowledge, but they are costly to analyze them, and new methods of sharing knowledge are needed. In addition, the interface using CG technology, which is used in surgical planning, is actively used as a means for doctors to easily obtain information, but it is not widely used for knowledge sharing. In this research, we aim to build a knowledge base to convey and utilize physicians’ know-how, which is difficult to convey, by accurately expressing empirical knowledge using CG technology. One of the challenges in sharing empirical knowledge is the difficulty of handling medical information from the viewpoint of personal information protection. Medical information is data that can easily identify individuals and that has a very high importance of rare data. Therefore, we examined the environment for using medical information and appropriate anonymization. First, we proposed a method for constructing an ontology for neurosurgery based on the medical ontology that has been studied in the medical field by organizing the structure of empirical knowledge of doctors. In addition, we designed and fabricated a prototype interface using 3D models as a system for data input and search display. We selected the glTF format as the 3D model format to be used in this study. In this paper, we report on the construction of a knowledge base for sharing empirical knowledge of neurosurgery, and the evaluation of the ontology constructed by the proposed method.

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References

  1. Gonçalves, J.M., et al.: Neuronavigation software to visualize and surgically approach brain structures. In: Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality (2018)

    Google Scholar 

  2. Khronos Group: gLTF Specification and Homepage. https://www.khronos.org/gltf/

  3. Mitsuhashi, N., et al.: BodyParts3D: 3D structure database for anatomical concepts. Nucleic Acids Res. 37(suppl\_1), D782–D785 (2009)

    Google Scholar 

  4. Scheuermann, R.H., Ceusters, W., Smith, B.: Toward an ontological treatment of disease and diagnosis. Summit Transl. Bioinform. 2009, 116 (2009)

    Google Scholar 

  5. StealthStation. https://www.medtronic.com/jpja/healthcareprofessionals/products/neurological/surgicalnavigationsystems/stealthstation/cranialneurosurgerynavigation.html

  6. Koeda, M., Nishimoto, S., Noborio, H., Watanabe, K.: Proposal and evaluation of AR-based microscopic brain surgery support system. In: Kurosu, M. (ed.) HCII 2019. LNCS, vol. 11567, pp. 458–468. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22643-5_36

    Chapter  Google Scholar 

  7. Afkari, H., et al.: The potentials for hands-free interaction in micro-neurosurgery. In: Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational (2014)

    Google Scholar 

  8. CesiumGS/obj2gltf: https://github.com/CesiumGS/obj2gltf

  9. Nakano, T.: Therapy of the insert32P into the pituitary tumor. J. Jpn. Soc. Head Neck Surg. 4(2), 123–127 (1994)

    Article  Google Scholar 

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Number JP20K12086.

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Correspondence to Ayuki Joto .

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Joto, A., Fuchi, T., Noborio, H., Onishi, K., Nonaka, M., Jozen, T. (2021). Construction of a Knowledge Base for Empirical Knowledge in Neurosurgery. In: Kurosu, M. (eds) Human-Computer Interaction. Interaction Techniques and Novel Applications. HCII 2021. Lecture Notes in Computer Science(), vol 12763. Springer, Cham. https://doi.org/10.1007/978-3-030-78465-2_38

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  • DOI: https://doi.org/10.1007/978-3-030-78465-2_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78464-5

  • Online ISBN: 978-3-030-78465-2

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